Best Big Data Integration Platforms

Shalaka Joshi
SJ
Researched and written by Shalaka Joshi

Big data integration platforms help facilitate and analyze big data integrations across cloud applications. They will typically facilitate the integration between big data processing solutions, applications and databases. Big data integration platforms usually require big data to have been processed prior to integration, but they facilitate the use of big data sets and insights. Companies use these to manage and store big data clusters and use them within cloud applications. They can help simplify the management of enormous amounts of data collected from IoT endpoints, applications, and communications. Some big data integration tools provide stream analytics capabilities, but provide more functionality for data management.

To qualify for inclusion in the Big Data Integration category, a product must:

Integrate big data processing data to external sources
Ingest and distribute large sets of homogenous and heterogenous data
Create a structured pipeline for big data management processes

Best Big Data Integration Platforms At A Glance

Best for Small Businesses:
Best for Mid-Market:
Best for Enterprise:
Highest User Satisfaction:
Best Free Software:
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Best for Enterprise:
Highest User Satisfaction:
Best Free Software:
G2 takes pride in showing unbiased reviews on user satisfaction in our ratings and reports. We do not allow paid placements in any of our ratings, rankings, or reports. Learn about our scoring methodologies.
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117 Listings in Big Data Integration Platforms Available
(986)4.5 out of 5
4th Easiest To Use in Big Data Integration Platforms software
View top Consulting Services for Google Cloud BigQuery
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Entry Level Price:Free
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    BigQuery is a serverless, multicloud data warehouse that simplifies the process of working with all types of data so you can focus on getting valuable business insights quickly. At the core of Google

    Users
    • Data Engineer
    • Software Engineer
    Industries
    • Computer Software
    • Information Technology and Services
    Market Segment
    • 39% Enterprise
    • 33% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Google Cloud BigQuery Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    373
    Performance
    189
    Speed
    188
    Fast Querying
    180
    Querying
    168
    Cons
    Expensive
    167
    Query Issues
    163
    Learning Curve
    108
    Cost Issues
    92
    Cost Management
    92
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Google Cloud BigQuery features and usability ratings that predict user satisfaction
    8.7
    Has the product been a good partner in doing business?
    Average: 8.9
    8.3
    Quality of Support
    Average: 8.9
    8.7
    Ease of Use
    Average: 8.8
    8.5
    Ease of Admin
    Average: 8.4
Product Description
How are these determined?Information
This description is provided by the seller.

BigQuery is a serverless, multicloud data warehouse that simplifies the process of working with all types of data so you can focus on getting valuable business insights quickly. At the core of Google

Users
  • Data Engineer
  • Software Engineer
Industries
  • Computer Software
  • Information Technology and Services
Market Segment
  • 39% Enterprise
  • 33% Mid-Market
Google Cloud BigQuery Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
373
Performance
189
Speed
188
Fast Querying
180
Querying
168
Cons
Expensive
167
Query Issues
163
Learning Curve
108
Cost Issues
92
Cost Management
92
Google Cloud BigQuery features and usability ratings that predict user satisfaction
8.7
Has the product been a good partner in doing business?
Average: 8.9
8.3
Quality of Support
Average: 8.9
8.7
Ease of Use
Average: 8.8
8.5
Ease of Admin
Average: 8.4
(543)4.5 out of 5
Optimized for quick response
3rd Easiest To Use in Big Data Integration Platforms software
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Entry Level Price:$2 Compute/Hour
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Snowflake delivers the Data Cloud — a global network where thousands of organizations mobilize data with near-unlimited scale, concurrency, and performance. Inside the Data Cloud, organizations unite

    Users
    • Data Engineer
    • Software Engineer
    Industries
    • Computer Software
    • Information Technology and Services
    Market Segment
    • 47% Enterprise
    • 41% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Snowflake Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    101
    Efficiency Improvement
    53
    Features
    50
    Data Management
    44
    Database Management
    42
    Cons
    Feature Limitations
    40
    Expensive
    37
    Limited Features
    31
    Query Issues
    24
    Missing Features
    23
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Snowflake features and usability ratings that predict user satisfaction
    9.0
    Has the product been a good partner in doing business?
    Average: 8.9
    8.6
    Quality of Support
    Average: 8.9
    9.0
    Ease of Use
    Average: 8.8
    8.5
    Ease of Admin
    Average: 8.4
Product Description
How are these determined?Information
This description is provided by the seller.

Snowflake delivers the Data Cloud — a global network where thousands of organizations mobilize data with near-unlimited scale, concurrency, and performance. Inside the Data Cloud, organizations unite

Users
  • Data Engineer
  • Software Engineer
Industries
  • Computer Software
  • Information Technology and Services
Market Segment
  • 47% Enterprise
  • 41% Mid-Market
Snowflake Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
101
Efficiency Improvement
53
Features
50
Data Management
44
Database Management
42
Cons
Feature Limitations
40
Expensive
37
Limited Features
31
Query Issues
24
Missing Features
23
Snowflake features and usability ratings that predict user satisfaction
9.0
Has the product been a good partner in doing business?
Average: 8.9
8.6
Quality of Support
Average: 8.9
9.0
Ease of Use
Average: 8.8
8.5
Ease of Admin
Average: 8.4
Syncari
SponsoredYou’re seeing this ad based on the product’s relevance to this page. Sponsored content does not receive preferential treatment in any of G2’s ratings.
(41)4.8 out of 5
Product Description
Syncari, a leader in data unification and automation, is modernizing enterprise master data management with its innovative Autonomous Data Management platform. Syncari is revolutionizing how enterpris
Syncari features and usability ratings that predict user satisfaction
10.0
Has the product been a good partner in doing business?
Average: 8.9
9.9
Quality of Support
Average: 8.9
7.9
Ease of Use
Average: 8.8
8.4
Ease of Admin
Average: 8.4
(392)4.3 out of 5
11th Easiest To Use in Big Data Integration Platforms software
View top Consulting Services for Amazon Redshift
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Entry Level Price:$1.22 - $3.26 Per hour
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Tens of thousands of customers use Amazon Redshift, a fast, fully managed, petabyte-scale data warehouse service that makes it simple and cost-effective to efficiently analyze all your data using your

    Users
    • Data Engineer
    • Senior Data Engineer
    Industries
    • Information Technology and Services
    • Computer Software
    Market Segment
    • 40% Enterprise
    • 37% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Amazon Redshift Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    43
    Scalability
    31
    Performance
    26
    Data Storage
    23
    Cost-Effective
    20
    Cons
    Expensive
    22
    Feature Limitations
    16
    Performance Issues
    12
    Cloud Limitations
    10
    SQL Limitations
    10
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Amazon Redshift features and usability ratings that predict user satisfaction
    8.8
    Has the product been a good partner in doing business?
    Average: 8.9
    8.5
    Quality of Support
    Average: 8.9
    8.7
    Ease of Use
    Average: 8.8
    8.5
    Ease of Admin
    Average: 8.4
Product Description
How are these determined?Information
This description is provided by the seller.

Tens of thousands of customers use Amazon Redshift, a fast, fully managed, petabyte-scale data warehouse service that makes it simple and cost-effective to efficiently analyze all your data using your

Users
  • Data Engineer
  • Senior Data Engineer
Industries
  • Information Technology and Services
  • Computer Software
Market Segment
  • 40% Enterprise
  • 37% Mid-Market
Amazon Redshift Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
43
Scalability
31
Performance
26
Data Storage
23
Cost-Effective
20
Cons
Expensive
22
Feature Limitations
16
Performance Issues
12
Cloud Limitations
10
SQL Limitations
10
Amazon Redshift features and usability ratings that predict user satisfaction
8.8
Has the product been a good partner in doing business?
Average: 8.9
8.5
Quality of Support
Average: 8.9
8.7
Ease of Use
Average: 8.8
8.5
Ease of Admin
Average: 8.4
Entry Level Price:Contact Us
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Simplify the complexity of how you B2B with webMethods.io B2B. The B2B integration allows you to share documents—purchase orders, invoices, shipping notices, contracts and more—in the cloud and keep e

    Users
    No information available
    Industries
    • Staffing and Recruiting
    • Computer Software
    Market Segment
    • 42% Mid-Market
    • 32% Enterprise
    User Sentiment
    How are these determined?Information
    These insights, currently in beta, are compiled from user reviews and grouped to display a high-level overview of the software.
    • webMethods.io B2B is a cloud-based solution that simplifies and automates business processes between partners, enabling efficient data and transaction exchange.
    • Users frequently mention the platform's user-friendly interface, strong security features, and its ability to integrate with various systems, which aids in efficient data sharing and communication between enterprises.
    • Users mentioned the initial learning curve, the complexity of customization options, and the high cost as potential challenges, particularly for small and medium businesses.
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • webMethods.io B2B Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    34
    Features
    17
    Integration Capabilities
    11
    Easy Integrations
    10
    Security
    10
    Cons
    Complexity
    17
    Expensive
    14
    Difficult Learning
    9
    Pricing Issues
    9
    Integration Issues
    6
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • webMethods.io B2B features and usability ratings that predict user satisfaction
    8.4
    Has the product been a good partner in doing business?
    Average: 8.9
    8.7
    Quality of Support
    Average: 8.9
    8.9
    Ease of Use
    Average: 8.8
    8.0
    Ease of Admin
    Average: 8.4
Product Description
How are these determined?Information
This description is provided by the seller.

Simplify the complexity of how you B2B with webMethods.io B2B. The B2B integration allows you to share documents—purchase orders, invoices, shipping notices, contracts and more—in the cloud and keep e

Users
No information available
Industries
  • Staffing and Recruiting
  • Computer Software
Market Segment
  • 42% Mid-Market
  • 32% Enterprise
User Sentiment
How are these determined?Information
These insights, currently in beta, are compiled from user reviews and grouped to display a high-level overview of the software.
  • webMethods.io B2B is a cloud-based solution that simplifies and automates business processes between partners, enabling efficient data and transaction exchange.
  • Users frequently mention the platform's user-friendly interface, strong security features, and its ability to integrate with various systems, which aids in efficient data sharing and communication between enterprises.
  • Users mentioned the initial learning curve, the complexity of customization options, and the high cost as potential challenges, particularly for small and medium businesses.
webMethods.io B2B Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
34
Features
17
Integration Capabilities
11
Easy Integrations
10
Security
10
Cons
Complexity
17
Expensive
14
Difficult Learning
9
Pricing Issues
9
Integration Issues
6
webMethods.io B2B features and usability ratings that predict user satisfaction
8.4
Has the product been a good partner in doing business?
Average: 8.9
8.7
Quality of Support
Average: 8.9
8.9
Ease of Use
Average: 8.8
8.0
Ease of Admin
Average: 8.4
(189)4.2 out of 5
View top Consulting Services for AWS Glue
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  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    AWS Glue is a serverless data integration service that makes it easier for analytics users to discover, prepare, move, and integrate data from multiple sources for analytics, machine learning, and app

    Users
    • Data Engineer
    • DevOps Engineer
    Industries
    • Information Technology and Services
    • Computer Software
    Market Segment
    • 49% Enterprise
    • 28% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • AWS Glue Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    77
    Data Integration
    52
    ETL Process
    43
    ETL Solutions
    38
    Easy Integrations
    34
    Cons
    Limited Functionality
    31
    Feature Limitations
    27
    AWS Dependency
    24
    Expensive
    22
    Lack of Features
    19
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • AWS Glue features and usability ratings that predict user satisfaction
    8.8
    Has the product been a good partner in doing business?
    Average: 8.9
    8.3
    Quality of Support
    Average: 8.9
    8.4
    Ease of Use
    Average: 8.8
    8.3
    Ease of Admin
    Average: 8.4
Product Description
How are these determined?Information
This description is provided by the seller.

AWS Glue is a serverless data integration service that makes it easier for analytics users to discover, prepare, move, and integrate data from multiple sources for analytics, machine learning, and app

Users
  • Data Engineer
  • DevOps Engineer
Industries
  • Information Technology and Services
  • Computer Software
Market Segment
  • 49% Enterprise
  • 28% Mid-Market
AWS Glue Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
77
Data Integration
52
ETL Process
43
ETL Solutions
38
Easy Integrations
34
Cons
Limited Functionality
31
Feature Limitations
27
AWS Dependency
24
Expensive
22
Lack of Features
19
AWS Glue features and usability ratings that predict user satisfaction
8.8
Has the product been a good partner in doing business?
Average: 8.9
8.3
Quality of Support
Average: 8.9
8.4
Ease of Use
Average: 8.8
8.3
Ease of Admin
Average: 8.4
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    AWS Lake Formation is a fully managed service to build, manage, secure, and share data in data lakes in days. You can centralize security and governance, and enable data sharing across the organizatio

    Users
    No information available
    Industries
    • Information Technology and Services
    Market Segment
    • 50% Small-Business
    • 33% Enterprise
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • AWS Lake Formation Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Data Storage
    10
    Ease of Use
    10
    Data Management
    5
    Data Security
    5
    Security
    5
    Cons
    Expensive
    4
    Difficult Setup
    3
    Difficulty
    3
    Complexity
    2
    Feature Limitations
    2
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • AWS Lake Formation features and usability ratings that predict user satisfaction
    9.0
    Has the product been a good partner in doing business?
    Average: 8.9
    8.3
    Quality of Support
    Average: 8.9
    8.7
    Ease of Use
    Average: 8.8
    8.0
    Ease of Admin
    Average: 8.4
Product Description
How are these determined?Information
This description is provided by the seller.

AWS Lake Formation is a fully managed service to build, manage, secure, and share data in data lakes in days. You can centralize security and governance, and enable data sharing across the organizatio

Users
No information available
Industries
  • Information Technology and Services
Market Segment
  • 50% Small-Business
  • 33% Enterprise
AWS Lake Formation Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Data Storage
10
Ease of Use
10
Data Management
5
Data Security
5
Security
5
Cons
Expensive
4
Difficult Setup
3
Difficulty
3
Complexity
2
Feature Limitations
2
AWS Lake Formation features and usability ratings that predict user satisfaction
9.0
Has the product been a good partner in doing business?
Average: 8.9
8.3
Quality of Support
Average: 8.9
8.7
Ease of Use
Average: 8.8
8.0
Ease of Admin
Average: 8.4
(231)4.8 out of 5
1st Easiest To Use in Big Data Integration Platforms software
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Entry Level Price:FREE
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Skyvia is a universal SaaS (Software as a Service) data platform for quick and easy solving a wide set of data-related tasks with no coding: data integration, automating workflows, cloud data backup,

    Users
    • CTO
    • CEO
    Industries
    • Information Technology and Services
    • Computer Software
    Market Segment
    • 56% Small-Business
    • 38% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Skyvia Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    69
    Easy Integrations
    38
    Data Management
    37
    Integrations
    35
    Features
    31
    Cons
    Feature Limitations
    15
    Data Limitations
    13
    Data Management
    10
    Error Reporting
    8
    Lack of Information
    8
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Skyvia features and usability ratings that predict user satisfaction
    9.3
    Has the product been a good partner in doing business?
    Average: 8.9
    9.2
    Quality of Support
    Average: 8.9
    9.3
    Ease of Use
    Average: 8.8
    9.4
    Ease of Admin
    Average: 8.4
Product Description
How are these determined?Information
This description is provided by the seller.

Skyvia is a universal SaaS (Software as a Service) data platform for quick and easy solving a wide set of data-related tasks with no coding: data integration, automating workflows, cloud data backup,

Users
  • CTO
  • CEO
Industries
  • Information Technology and Services
  • Computer Software
Market Segment
  • 56% Small-Business
  • 38% Mid-Market
Skyvia Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
69
Easy Integrations
38
Data Management
37
Integrations
35
Features
31
Cons
Feature Limitations
15
Data Limitations
13
Data Management
10
Error Reporting
8
Lack of Information
8
Skyvia features and usability ratings that predict user satisfaction
9.3
Has the product been a good partner in doing business?
Average: 8.9
9.2
Quality of Support
Average: 8.9
9.3
Ease of Use
Average: 8.8
9.4
Ease of Admin
Average: 8.4
(65)4.7 out of 5
2nd Easiest To Use in Big Data Integration Platforms software
Save to My Lists
Entry Level Price:Starting at $49.00
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Coefficient is a sidebar app for Google Sheets and Excel. Connect to your business systems, import live data, automate workflows, and export data back to your business systems. > Connect any data

    Users
    No information available
    Industries
    • Information Technology and Services
    • Computer Software
    Market Segment
    • 48% Mid-Market
    • 37% Small-Business
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Coefficient Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    37
    Automation
    14
    Data Integration
    9
    Easy Integrations
    8
    Reporting
    8
    Cons
    Feature Limitations
    13
    Table Limitations
    7
    Lagging Issues
    4
    Query Issues
    4
    Access Control
    3
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Coefficient features and usability ratings that predict user satisfaction
    9.5
    Has the product been a good partner in doing business?
    Average: 8.9
    9.1
    Quality of Support
    Average: 8.9
    9.3
    Ease of Use
    Average: 8.8
    9.4
    Ease of Admin
    Average: 8.4
Product Description
How are these determined?Information
This description is provided by the seller.

Coefficient is a sidebar app for Google Sheets and Excel. Connect to your business systems, import live data, automate workflows, and export data back to your business systems. > Connect any data

Users
No information available
Industries
  • Information Technology and Services
  • Computer Software
Market Segment
  • 48% Mid-Market
  • 37% Small-Business
Coefficient Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
37
Automation
14
Data Integration
9
Easy Integrations
8
Reporting
8
Cons
Feature Limitations
13
Table Limitations
7
Lagging Issues
4
Query Issues
4
Access Control
3
Coefficient features and usability ratings that predict user satisfaction
9.5
Has the product been a good partner in doing business?
Average: 8.9
9.1
Quality of Support
Average: 8.9
9.3
Ease of Use
Average: 8.8
9.4
Ease of Admin
Average: 8.4
(105)4.6 out of 5
Optimized for quick response
7th Easiest To Use in Big Data Integration Platforms software
Save to My Lists
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    For data teams looking to increase the availability of trusted data, Astronomer provides Astro, the modern data orchestration platform, powered by Airflow. Astro enables data engineers, data scientist

    Users
    • Data Engineer
    • Senior Data Engineer
    Industries
    • Information Technology and Services
    • Computer Software
    Market Segment
    • 48% Mid-Market
    • 37% Enterprise
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Astro by Astronomer Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    62
    Easy Setup
    33
    Customer Support
    29
    User Interface
    26
    Implementation Ease
    20
    Cons
    Expensive
    19
    Feature Limitations
    17
    Lacking Features
    17
    Limited Features
    15
    Missing Features
    14
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Astro by Astronomer features and usability ratings that predict user satisfaction
    9.1
    Has the product been a good partner in doing business?
    Average: 8.9
    9.1
    Quality of Support
    Average: 8.9
    9.0
    Ease of Use
    Average: 8.8
    9.0
    Ease of Admin
    Average: 8.4
Product Description
How are these determined?Information
This description is provided by the seller.

For data teams looking to increase the availability of trusted data, Astronomer provides Astro, the modern data orchestration platform, powered by Airflow. Astro enables data engineers, data scientist

Users
  • Data Engineer
  • Senior Data Engineer
Industries
  • Information Technology and Services
  • Computer Software
Market Segment
  • 48% Mid-Market
  • 37% Enterprise
Astro by Astronomer Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
62
Easy Setup
33
Customer Support
29
User Interface
26
Implementation Ease
20
Cons
Expensive
19
Feature Limitations
17
Lacking Features
17
Limited Features
15
Missing Features
14
Astro by Astronomer features and usability ratings that predict user satisfaction
9.1
Has the product been a good partner in doing business?
Average: 8.9
9.1
Quality of Support
Average: 8.9
9.0
Ease of Use
Average: 8.8
9.0
Ease of Admin
Average: 8.4
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Azure Data Factory (ADF) is a service designed to allow developers to integrate disparate data sources. It provides access to on-premises data in SQL Server and cloud data in Azure Storage (Blob and T

    Users
    • Data Engineer
    • Software Engineer
    Industries
    • Information Technology and Services
    • Computer Software
    Market Segment
    • 61% Enterprise
    • 30% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Azure Data Factory Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    20
    Data Integration
    12
    Drag
    10
    ETL Efficiency
    9
    ETL Process
    9
    Cons
    Feature Limitations
    8
    Complex Usability
    4
    Error Reporting
    4
    Complexity
    3
    Debugging Difficulty
    3
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Azure Data Factory features and usability ratings that predict user satisfaction
    9.4
    Has the product been a good partner in doing business?
    Average: 8.9
    8.8
    Quality of Support
    Average: 8.9
    8.9
    Ease of Use
    Average: 8.8
    8.4
    Ease of Admin
    Average: 8.4
Product Description
How are these determined?Information
This description is provided by the seller.

Azure Data Factory (ADF) is a service designed to allow developers to integrate disparate data sources. It provides access to on-premises data in SQL Server and cloud data in Azure Storage (Blob and T

Users
  • Data Engineer
  • Software Engineer
Industries
  • Information Technology and Services
  • Computer Software
Market Segment
  • 61% Enterprise
  • 30% Mid-Market
Azure Data Factory Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
20
Data Integration
12
Drag
10
ETL Efficiency
9
ETL Process
9
Cons
Feature Limitations
8
Complex Usability
4
Error Reporting
4
Complexity
3
Debugging Difficulty
3
Azure Data Factory features and usability ratings that predict user satisfaction
9.4
Has the product been a good partner in doing business?
Average: 8.9
8.8
Quality of Support
Average: 8.9
8.9
Ease of Use
Average: 8.8
8.4
Ease of Admin
Average: 8.4
Entry Level Price:Contact Us
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    StreamSets, a Software AG company, eliminates data integration friction in complex hybrid and multi-cloud environments to keep pace with need-it-now business data demands. Our platform lets data teams

    Users
    • Data Engineer
    Industries
    • Information Technology and Services
    • Computer Software
    Market Segment
    • 47% Enterprise
    • 32% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • StreamSets Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    40
    Data Management
    33
    Data Pipelining
    27
    Integrations
    21
    User Interface
    18
    Cons
    Feature Limitations
    12
    Limitations
    12
    Connector Issues
    10
    Learning Curve
    9
    Missing Features
    9
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • StreamSets features and usability ratings that predict user satisfaction
    8.1
    Has the product been a good partner in doing business?
    Average: 8.9
    8.0
    Quality of Support
    Average: 8.9
    8.5
    Ease of Use
    Average: 8.8
    7.9
    Ease of Admin
    Average: 8.4
Product Description
How are these determined?Information
This description is provided by the seller.

StreamSets, a Software AG company, eliminates data integration friction in complex hybrid and multi-cloud environments to keep pace with need-it-now business data demands. Our platform lets data teams

Users
  • Data Engineer
Industries
  • Information Technology and Services
  • Computer Software
Market Segment
  • 47% Enterprise
  • 32% Mid-Market
StreamSets Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
40
Data Management
33
Data Pipelining
27
Integrations
21
User Interface
18
Cons
Feature Limitations
12
Limitations
12
Connector Issues
10
Learning Curve
9
Missing Features
9
StreamSets features and usability ratings that predict user satisfaction
8.1
Has the product been a good partner in doing business?
Average: 8.9
8.0
Quality of Support
Average: 8.9
8.5
Ease of Use
Average: 8.8
7.9
Ease of Admin
Average: 8.4
(31)4.8 out of 5
5th Easiest To Use in Big Data Integration Platforms software
Save to My Lists
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Imagine if you could have all your favorite data tools as a single platform that's incredibly easy to use? Data is one of the most fragmented industries, with over 500 vendors in 15+ categories. T

    Users
    No information available
    Industries
    • Financial Services
    Market Segment
    • 68% Mid-Market
    • 32% Small-Business
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • 5X Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    22
    Customer Support
    18
    Features
    10
    Easy Setup
    8
    Cost-Effective
    7
    Cons
    Feature Limitations
    3
    Missing Features
    3
    Data Management
    1
    Difficult Setup
    1
    Expensive
    1
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • 5X features and usability ratings that predict user satisfaction
    9.6
    Has the product been a good partner in doing business?
    Average: 8.9
    9.6
    Quality of Support
    Average: 8.9
    9.3
    Ease of Use
    Average: 8.8
    9.3
    Ease of Admin
    Average: 8.4
Product Description
How are these determined?Information
This description is provided by the seller.

Imagine if you could have all your favorite data tools as a single platform that's incredibly easy to use? Data is one of the most fragmented industries, with over 500 vendors in 15+ categories. T

Users
No information available
Industries
  • Financial Services
Market Segment
  • 68% Mid-Market
  • 32% Small-Business
5X Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
22
Customer Support
18
Features
10
Easy Setup
8
Cost-Effective
7
Cons
Feature Limitations
3
Missing Features
3
Data Management
1
Difficult Setup
1
Expensive
1
5X features and usability ratings that predict user satisfaction
9.6
Has the product been a good partner in doing business?
Average: 8.9
9.6
Quality of Support
Average: 8.9
9.3
Ease of Use
Average: 8.8
9.3
Ease of Admin
Average: 8.4
(326)4.5 out of 5
Optimized for quick response
9th Easiest To Use in Big Data Integration Platforms software
Save to My Lists
Entry Level Price:Free
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    Census is the first Universal Data Platform that brings data transformation, activation, and governance into one collaborative workspace. Leading enterprises including HubSpot, Activision, Canva, Oran

    Users
    • Data Analyst
    • Analytics Engineer
    Industries
    • Computer Software
    • Information Technology and Services
    Market Segment
    • 62% Mid-Market
    • 24% Small-Business
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • Census Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    188
    Easy Integration
    83
    Easy Setup
    65
    User Interface
    63
    Customer Support
    51
    Cons
    Sync Issues
    59
    Learning Curve
    28
    Expensive
    27
    Integration Issues
    27
    Feature Limitations
    22
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • Census features and usability ratings that predict user satisfaction
    9.3
    Has the product been a good partner in doing business?
    Average: 8.9
    9.2
    Quality of Support
    Average: 8.9
    9.0
    Ease of Use
    Average: 8.8
    8.9
    Ease of Admin
    Average: 8.4
Product Description
How are these determined?Information
This description is provided by the seller.

Census is the first Universal Data Platform that brings data transformation, activation, and governance into one collaborative workspace. Leading enterprises including HubSpot, Activision, Canva, Oran

Users
  • Data Analyst
  • Analytics Engineer
Industries
  • Computer Software
  • Information Technology and Services
Market Segment
  • 62% Mid-Market
  • 24% Small-Business
Census Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
188
Easy Integration
83
Easy Setup
65
User Interface
63
Customer Support
51
Cons
Sync Issues
59
Learning Curve
28
Expensive
27
Integration Issues
27
Feature Limitations
22
Census features and usability ratings that predict user satisfaction
9.3
Has the product been a good partner in doing business?
Average: 8.9
9.2
Quality of Support
Average: 8.9
9.0
Ease of Use
Average: 8.8
8.9
Ease of Admin
Average: 8.4
(154)4.8 out of 5
Save to My Lists
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    dbt is a transformation workflow that lets data teams quickly and collaboratively deploy analytics code following software engineering best practices like modularity, portability, CI/CD, and documenta

    Users
    • Analytics Engineer
    • Data Engineer
    Industries
    • Computer Software
    • Information Technology and Services
    Market Segment
    • 60% Mid-Market
    • 25% Small-Business
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • dbt Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    92
    Features
    46
    Productivity Improvement
    36
    Documentation
    35
    Automation
    34
    Cons
    Feature Limitations
    36
    Limited Functionality
    32
    Missing Features
    24
    Learning Curve
    22
    Learning Difficulty
    17
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • dbt features and usability ratings that predict user satisfaction
    8.9
    Has the product been a good partner in doing business?
    Average: 8.9
    8.9
    Quality of Support
    Average: 8.9
    9.0
    Ease of Use
    Average: 8.8
    8.4
    Ease of Admin
    Average: 8.4
Product Description
How are these determined?Information
This description is provided by the seller.

dbt is a transformation workflow that lets data teams quickly and collaboratively deploy analytics code following software engineering best practices like modularity, portability, CI/CD, and documenta

Users
  • Analytics Engineer
  • Data Engineer
Industries
  • Computer Software
  • Information Technology and Services
Market Segment
  • 60% Mid-Market
  • 25% Small-Business
dbt Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
92
Features
46
Productivity Improvement
36
Documentation
35
Automation
34
Cons
Feature Limitations
36
Limited Functionality
32
Missing Features
24
Learning Curve
22
Learning Difficulty
17
dbt features and usability ratings that predict user satisfaction
8.9
Has the product been a good partner in doing business?
Average: 8.9
8.9
Quality of Support
Average: 8.9
9.0
Ease of Use
Average: 8.8
8.4
Ease of Admin
Average: 8.4
(267)4.3 out of 5
Optimized for quick response
15th Easiest To Use in Big Data Integration Platforms software
Save to My Lists
  • Overview
    Expand/Collapse Overview
  • Product Description
    How are these determined?Information
    This description is provided by the seller.

    SnapLogic is the leader in generative integration. As a pioneer in AI-led integration, the SnapLogic Platform accelerates digital transformation across the enterprise and empowers everyone to integrat

    Users
    • Consultant
    • Data Engineer
    Industries
    • Information Technology and Services
    • Computer Software
    Market Segment
    • 48% Enterprise
    • 34% Mid-Market
  • Pros and Cons
    Expand/Collapse Pros and Cons
  • SnapLogic Intelligent Integration Platform (IIP) Pros and Cons
    How are these determined?Information
    Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
    Pros
    Ease of Use
    84
    Integrations
    49
    Easy Integrations
    44
    Features
    36
    Connectors
    35
    Cons
    Performance Issues
    20
    Complexity
    18
    Poor UI
    18
    Poor User Interface
    18
    Lagging Issues
    17
  • User Satisfaction
    Expand/Collapse User Satisfaction
  • SnapLogic Intelligent Integration Platform (IIP) features and usability ratings that predict user satisfaction
    8.7
    Has the product been a good partner in doing business?
    Average: 8.9
    8.2
    Quality of Support
    Average: 8.9
    8.7
    Ease of Use
    Average: 8.8
    8.5
    Ease of Admin
    Average: 8.4
Product Description
How are these determined?Information
This description is provided by the seller.

SnapLogic is the leader in generative integration. As a pioneer in AI-led integration, the SnapLogic Platform accelerates digital transformation across the enterprise and empowers everyone to integrat

Users
  • Consultant
  • Data Engineer
Industries
  • Information Technology and Services
  • Computer Software
Market Segment
  • 48% Enterprise
  • 34% Mid-Market
SnapLogic Intelligent Integration Platform (IIP) Pros and Cons
How are these determined?Information
Pros and Cons are compiled from review feedback and grouped into themes to provide an easy-to-understand summary of user reviews.
Pros
Ease of Use
84
Integrations
49
Easy Integrations
44
Features
36
Connectors
35
Cons
Performance Issues
20
Complexity
18
Poor UI
18
Poor User Interface
18
Lagging Issues
17
SnapLogic Intelligent Integration Platform (IIP) features and usability ratings that predict user satisfaction
8.7
Has the product been a good partner in doing business?
Average: 8.9
8.2
Quality of Support
Average: 8.9
8.7
Ease of Use
Average: 8.8
8.5
Ease of Admin
Average: 8.4
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Learn More About Big Data Integration Platforms

What are Big Data Integration Platforms?

Big data integration is defined as a process within the data lifecycle that involves extracting data from heterogeneous sources and combining it to obtain insightful unified information which can aid in better decision making. 

Big data integration platforms are the tools that allow data to be extracted from various data sources and then sort and process it. There is a huge volume of data generated from various sources daily. Organizations are trying to capture value out of this data. Most of the data comes in an unstructured format. Required data is often distributed across various sources like IoT endpoints, applications, communications, or provided by third parties. 

What Types of Big Data Integration Platforms Exist?

The end goal of a big data integration platform is to transfer and unify data from disparate sources. Data managers can get a better understanding of various methods of achieving this goal by understanding the different types of data integration software. They can decide which type of platform suits them the most: 

Middleware data integration

Middleware is a software that acts as a binding material for two different systems. It connects various applications and transfers data from application to database. Middleware is widely in use for application integration and data management. When an organization is integrating legacy systems with modern ones, middleware is used. 

Data consolidation

This term is interchangeably used with data integration. Data consolidation means combining data from all disparate sources. It also removes any errors before storing it in a data warehouse or data lake. Data consolidation improves data quality.

Extract, transform and load (ETL)

ETL forms the core of data integration tools even today. ETL is the process of consolidation of data in a data warehouse. It involves extracting the data from source systems, transforming it into the required format, and loading it to the target system.

Enterprise data integration

While big data integration is a broader term, enterprise data integration refers to the centralization of data across multiple organizations. This is usually done when the organizations go through mergers and acquisitions. 

What are the Common Features of Big Data Integration Platforms?

Big data integration software is one way for any organization to make informed decisions. Below are key features of big data integration platforms:

Big data connectors: Many applications use more than one database nowadays. Data connectors make it possible to move data from one database to another. Organizations use big data connectors to filter and transform data in a proper structure for querying and analyzing purposes. Organizations can benefit from the scalability and real-time data transmissions unlike that of traditional batches. With cloud-based and data-driven businesses gaining popularity, advanced data integration in any big data integration platform helps with more agile integrations, without constant schema changes. IPaaS provides pre-built big data connectors, business rules, and maps, which help organize integration flows. 

Data transformation: Data transformation is the process of changing data from one format structure into another. Organizations use this tool to organize the data better by making it compatible with other data, joining data, and so on. The processes such as data integration, data migration, data warehousing/data storage, and data wrangling all may involve data transformation.

Leverage data from unconventional sources of big data: This is one of the key features of any efficient big data integration platform. Common file formats like PDFs are usually supported by data integration tools. The advanced feature of leveraging data from unconventional sources supports file formats like COBOL, email sources, and XML/JSON files. Organizations use this feature to obtain streamlined data analysis.

Data virtualization: Organizations benefit from this feature by getting access to a unified view of various disparate systems. There is no physical movement of data to and from databases. The feature gives organizations real-time access to their data without exposing the technical details of the source systems.

Data quality: This feature is central to all the big data integration platforms. When data is of excellent quality, it is easier to process and analyze, ultimately helping organizations to make better decisions.

Database integration: Database technology aids in data storage and has evolved over the years. Relational, NoSQL, hierarchical, and many more are types of databases. NoSQL database is also known as a non-relational database. Database integration is usually done in cases of mergers and acquisitions. Two individual databases are integrated for a better understanding of new business.

Big data management: It is the organization, administration, and governance of large volumes of structured and unstructured data. Data governance is a major part of data management. A big data governance strategy plays a key role in determining how the business will benefit from available resources. Organizations leverage this feature to ensure a high level of data quality. 

Data processing: The feature manipulates data by collecting and combining it to obtain usable information. With big data migrating to the cloud, the benefits of cloud data processing can be reaped by small and large organizations alike.

Application programming interface (API): This feature connects one system to another via APIs, allowing the data exchange between those two systems. It facilitates seamless connectivity between devices and programs.

Data warehouse: This is a part of the data integration process which deals with cleansing, formatting, and data storage. One of the important implementations of big data integration is building a data warehouse. It is done by merging systems to unify the data from disparate sources. Technically data warehouses perform queries and analysis.

What are the Benefits of Big Data Integration Platforms?

Businesses today are data-driven. Hence, it is important to clean, process, and organize this data for better decision-making. Following are the benefits of implementing big data integration platforms at organizations: 

Reducing the complexity of big data: In any organization, the more the number of applications, the more are the number of interfaces. Big data can be difficult to manage at times. However, big data integration software helps in managing complexity, making easier delivery of data to any system, and streamlining the connections. It begins with defining business-critical data; data related to customers, products, sites, and suppliers. The overall process might involve updating, collating, and refining data to form a uniform understanding of the same. 

Scalability: Big data is primarily unstructured and requires real-time analysis. Advanced big data tools in association with cloud computing aid in connecting the data with real-time events and automate resource allocation based on integration activities. When organizations have scalable data platforms, they are also prepared for potential growth in their data needs.

Better decision making: Organizations often deal with a variety of data from disparate sources. Data integration helps managers understand the dynamics of their business and anticipate shifts in the market. Data entered manually can often have flaws and thus poor insights going further. Integration platforms help in obtaining up-to-date data, thus facilitating faster and higher quality decision making. When data is unified, it is available for everyone in the organization to access. This boosts transparency, collaboration, and ultimately maximizes data value. 

Cost optimization: Integration platforms create a centralized software architecture that connects to system and software and allows transporting data seamlessly. This focuses on eliminating inefficiencies caused due to using multiple software within an organization. This brings down the cost required for storing, processing, and analyzing large amounts of data.

Data governance: This system helps in understanding the executives in charge of data assets in an organization. 

Who Uses Big Data Integration Platforms?

Data analysts and data scientists: These employees are generally the main users of big data integration tools. They use the software to gather a deeper understanding of business-critical data. These teams may be tasked with data preparation, cleansing, and data processing for further analysis.

Marketing teams: Marketing teams often run different types of campaigns, including email marketing, digital advertising, or even traditional advertising campaigns. The data that is error free and insightful helps the marketing team to execute successful campaigns and strategies. Big data integration helps the marketing teams promote the company or its product to the target audience.

Finance teams: Finance teams leverage data integration platforms to gain insight and understanding into the factors that impact an organization's business. Finance teams require real-time data for obtaining actionable insights which is possible using advanced data integration software. By integrating financial data with other operations data, accounting and finance teams pull actionable insights that might not have been uncovered through the use of traditional tools.

Software Related to Big Data Integration Platforms

Related solutions that can be used together with data integration include:

Metadata-driven data integration software: Big data integration software can handle a variety of data. However, when used with powerful metadata, it can streamline the creation and management of BI reporting. Metadata repository provides a view and analyses the movement of data around the organization.

Data management platforms: This category of software is used to gather, analyze, and store big data. Data management platforms help organizations leverage big data from various sources in real time leading to effective customer engagement.

Data replication software: Data replication can be one-time or an ongoing process. This software aims at keeping all the members of the organization on the same page. Data replication involves copying data from one server to a database on another server.

Big data analytics software: Data Analytics platforms are a great aid to any organization with the need for timely data visualization of high-level analytics. Many industries target their customers using data analytics which helps the companies provide a customized experience and meet customer expectations.

Application integration software: Application integration, like data integration, works in batches; this leaves gaps in taking quick actions. Organizations can benefit from moving data in real time with application integration to easy access and quicker actions.

Challenges with Big Data Integration Platforms

Managing large data volume: The exponential growth of data from various sources is one of the biggest challenges of big data integration. This further creates issues with the retention of this data. Sometimes data runs on multiple platforms—a combination of on-premises and cloud hosting. This gives rise to complexity and managing can become difficult.

Manual data integration tasks: In many organizations, data scientists are the employees finding and preparing the data, which leaves an equivalent to only a week’s time for actual data science tasks and analytical work. This has made enterprises look for tools to automate ingestion and integration.

Growth of heterogeneous data: Heterogeneous data is a group of data with non-similar data types. Data is collected in different formats—structured, unstructured, and semi-structured. Integrating all these disparate data types is a tedious process and would need a proper ETL tool. Data is mostly handled by various data handling systems and it may not be in the same format.

Issues with data quality: Incompatible or invalid data may be present in the data obtained from disparate sources. Businesses might not be aware of this, and the analytics might show insights with this incompatible data which could have severe repercussions. The insights provided by data analytics could potentially be misleading. The quality of gathered data is kept in check by appointing an executive for data management. This manual job can be time consuming for huge volumes of data.

Which Companies Should Buy Big Data Integration Platforms?

Retail: This industry is the most common one to use big data software. They want to attract more customers to their business. For that, they need to correctly anticipate what the customers want. Accurate insights can help companies to identify their target customers as well as build on their competitive advantage.

Logistics: Data Integration brings different systems together by combining data and functions. Data in the transportation and logistics industry is stored in on-premises ERP and cloud-based CRM systems. Big data integration solutions help organizations overcome challenges like traffic congestion and mismanagement of capacity using automated fleet management and cloud-based analytics. Business processes are optimized and transcription errors are also reduced.

Education: Data privacy and security are of utmost importance in the education industry. Big data tools are changing the educational scenario altogether. Cutting-edge technology can help make better educational assessments. 

Banking and finance: Data integration helps banks in providing better customer experience, cross-selling, customer retention, and overall profitability. Big data integration helps in fraud detection and compliance.

Construction: Large infrastructure projects are huge in volume. While construction is one of the least digitized industries, organizations are now realizing the importance of the data that is generated and that it should be leveraged for obtaining better results. Using big data integration platforms, companies can combine design and construction data so that every department remains on the same page. This leads to better tracking of project design data being used at the construction site.

Healthcare: Big data platforms are critical to the healthcare industry. The data in healthcare is unstructured and data integration can prove useful in obtaining valuable insights. The ultimate goal of data integration solutions in this industry is to improve the quality and cost of healthcare for patients and researchers.

How to Buy Big Data Integration Platforms?

Requirements Gathering (RFI/RFP) for Big Data Integration Platforms

If a company is just starting out and looking to purchase the first big data integration platform, or maybe an organization needs to update a legacy system--wherever a business is in its buying process, g2.com can help select the best big data integration software for the business.

The particular business pain points might be related to all of the manual work that must be completed. If the company has amassed a lot of data, the need is to look for a solution that can grow with the organization. Users should think about the pain points and jot them down; these should be used to help create a checklist of criteria. Additionally, the buyer must determine the number of employees who will need to use the big data integration tool, as this drives the number of licenses they are likely to buy.

Taking a holistic overview of the business and identifying pain points can help the team springboard into creating a checklist of criteria. The checklist serves as a detailed guide that includes both necessary and nice-to-have features including budget features, number of users, integrations, security requirements, cloud or on-premises solutions, and more.

Depending on the scope of the deployment, it might be helpful to produce an RFI, a one-page list with a few bullet points describing what is needed from a big data integration platform.

Compare Big Data Integration Platforms Products

Create a long list

From meeting the business functionality needs to implementation, vendor evaluations are an essential part of the software buying process. For ease of comparison after all demos are complete, it helps to prepare a consistent list of questions regarding specific needs and concerns to ask each vendor.

Create a short list

From the long list of vendors, it is helpful to narrow down the list of vendors and come up with a shorter list of contenders, preferably no more than three to five. With this list in hand, businesses can produce a matrix to compare the features and pricing of the various big data integration solutions.

Conduct demos

To ensure the comparison is thorough, the user should demo each solution on the shortlist with the same use case and datasets. This will allow the business to evaluate like for like and see how each vendor stacks up against the competition.

Selection of Big Data Integration Platforms

Choose a selection team

Before getting started, it's crucial to create a team that will work together throughout the entire process, from identifying pain points to implementation. The software selection team should consist of members of the organization who have the right interest, skills, and time to participate in this process. A team of three to five people with roles such as the main decision maker, project manager, process owner, system owner, or staffing subject matter expert, as well as a technical lead, IT administrator would suffice. In smaller companies, the vendor selection team may be smaller, with fewer participants multitasking and taking on more responsibilities.

Negotiation

As data integration platforms are all about the data, the user must make sure that the selection process is data driven as well. The selection team should compare important data like pricing metrics of a particular vendor, the stage that buyer organization is in, and also terms and conditions of the organization.

Final decision

It is imperative to open up a conversation regarding pricing and licensing. For example, the vendor may be willing to give a discount for multi-year contracts or for recommending the product to others.

What Do Big Data Integration Platforms Cost?

Data Integration software is available both on-premises and on cloud. The cost per type changes given there are certain factors for each type to consider. The organizations that consider deploying on-premises software are liable for costs associated with server hardware, power consumption, and space. Whereas software using the cloud can be charged for the resources it uses and prices go up or down depending on how much of the software is consumed. 

Return on Investment (ROI)

Organizations buy big data integration platforms with an expectation of a certain ROI. Although there are ways to directly calculate ROIs, it could be a little daunting to use those here. It entirely depends on the intricacy of the project and ultimately the software itself. ROI can be further looked at from an IT perspective and a business perspective. The ROI on IT infrastructure, staffing, expertise-building, and services cost is calculated. Whereas, for business, time investments, outside investments (the cost related to external partners involved in the project), and opportunity costs are treated as important.

Implementation of Big Data Integration Platforms

How are Big Data Integration Platforms Implemented?

It is necessary to define the goals to be achieved using a big data integration platform. This will help measure the success of target projects for which big data integration software will be used. Large organizations have data in large volumes from heterogeneous data sources, hence it is better to hire an external party for implementing the software. Connectivity between systems is ensured during the process. With a rich experience throughout the years, the specialists from these consultancy firms can guide the businesses in connecting and consolidating their data effectively by helping the company to identify the best vendors in the space that would suit their business needs and goals.

Who is Responsible for Big Data Integration Platforms Implementation?

Data integration implementation can be a tedious process. In such times, it is advisable to have vendor support throughout the implementation. The team size could range from moderate to large depending on the complexity of the software being implemented. With cross-functional teams, it is possible to streamline the implementation process. Before actual use, it is always a good practice to test sample data.

What Does the Implementation Process Look Like for Big Data Integration Platforms?

The overall implementation process can be done in the following steps:

  • Identifying and defining the project is a step when organizations can figure out the format in which the consolidated data has to be in so that it can prove of maximum usefulness to the organization.
  • Reviewing the systems becomes crucial at this point. Depending on the connectivity, the consultancy specialists may advise on data connectors and/or SFTP ports to facilitate data interchange.
  • Defining data integration framework.
  • Defining how data will be processed.

When Should You Implement Big Data Integration Platforms?

Big data integration software is usually required when the organization deals with loads of data coming from disparate sources.