Apache Spark

Apache Spark

Apache Software Foundation
Spark Streaming

Spark Streaming

Apache Software Foundation
python-sql

python-sql

Python Software Foundation
+

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About

Apache Spark™ is a unified analytics engine for large-scale data processing. Apache Spark achieves high performance for both batch and streaming data, using a state-of-the-art DAG scheduler, a query optimizer, and a physical execution engine. Spark offers over 80 high-level operators that make it easy to build parallel apps. And you can use it interactively from the Scala, Python, R, and SQL shells. Spark powers a stack of libraries including SQL and DataFrames, MLlib for machine learning, GraphX, and Spark Streaming. You can combine these libraries seamlessly in the same application. Spark runs on Hadoop, Apache Mesos, Kubernetes, standalone, or in the cloud. It can access diverse data sources. You can run Spark using its standalone cluster mode, on EC2, on Hadoop YARN, on Mesos, or on Kubernetes. Access data in HDFS, Alluxio, Apache Cassandra, Apache HBase, Apache Hive, and hundreds of other data sources.

About

Spark Streaming brings Apache Spark's language-integrated API to stream processing, letting you write streaming jobs the same way you write batch jobs. It supports Java, Scala and Python. Spark Streaming recovers both lost work and operator state (e.g. sliding windows) out of the box, without any extra code on your part. By running on Spark, Spark Streaming lets you reuse the same code for batch processing, join streams against historical data, or run ad-hoc queries on stream state. Build powerful interactive applications, not just analytics. Spark Streaming is developed as part of Apache Spark. It thus gets tested and updated with each Spark release. You can run Spark Streaming on Spark's standalone cluster mode or other supported cluster resource managers. It also includes a local run mode for development. In production, Spark Streaming uses ZooKeeper and HDFS for high availability.

About

python-sql is a library to write SQL queries in a pythonic way. Simple selects, select with where condition. Select with join or select with multiple joins. Select with group_by and select with output name. Select with order_by, or select with sub-select. Select on other schema and insert query with default values. Insert query with values, and insert query with query. Update query with values. Update query with where condition. Update query with from the list. Delete query with where condition, and delete query with sub-query. Provides limit style, qmark style, and numeric style.

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Organizations that want a unified analytics engine for large-scale data processing

Audience

Real-Time Data Streaming solution for businesses

Audience

Developers searching for a solution offering a library to write SQL queries

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

Support

Phone Support
24/7 Live Support
Online

API

Offers API

API

Offers API

API

Offers API

Screenshots and Videos

Screenshots and Videos

Screenshots and Videos

Pricing

No information available.
Free Version
Free Trial

Pricing

No information available.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

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Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Reviews/Ratings

Overall 0.0 / 5
ease 0.0 / 5
features 0.0 / 5
design 0.0 / 5
support 0.0 / 5

This software hasn't been reviewed yet. Be the first to provide a review:

Review this Software

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Apache Software Foundation
Founded: 1999
United States
spark.apache.org

Company Information

Apache Software Foundation
Founded: 1999
United States
spark.apache.org/streaming/

Company Information

Python Software Foundation
United States
pypi.org/project/python-sql/

Alternatives

dbt

dbt

dbt Labs

Alternatives

ksqlDB

ksqlDB

Confluent

Alternatives

AWS Glue

AWS Glue

Amazon
Samza

Samza

Apache Software Foundation
Apache Spark

Apache Spark

Apache Software Foundation
MLlib

MLlib

Apache Software Foundation
NGS-IQ

NGS-IQ

New Generation Software
MLlib

MLlib

Apache Software Foundation

Categories

Categories

Categories

Streaming Analytics Features

Data Enrichment
Data Wrangling / Data Prep
Multiple Data Source Support
Process Automation
Real-time Analysis / Reporting
Visualization Dashboards

Integrations

Actian Avalanche
Acxiom InfoBase
Acxiom Real Identity
Apache Hudi
Baidu AI Cloud Stream Computing
BigLake
Domino Enterprise MLOps Platform
Hue
IBM SPSS Modeler
Kubernetes
Medical LLM
Occubee
Quorso
RazorThink
Tabular
TeamStation
Timbr.ai
Yandex Data Proc
eQube®-DaaS

Integrations

Actian Avalanche
Acxiom InfoBase
Acxiom Real Identity
Apache Hudi
Baidu AI Cloud Stream Computing
BigLake
Domino Enterprise MLOps Platform
Hue
IBM SPSS Modeler
Kubernetes
Medical LLM
Occubee
Quorso
RazorThink
Tabular
TeamStation
Timbr.ai
Yandex Data Proc
eQube®-DaaS

Integrations

Actian Avalanche
Acxiom InfoBase
Acxiom Real Identity
Apache Hudi
Baidu AI Cloud Stream Computing
BigLake
Domino Enterprise MLOps Platform
Hue
IBM SPSS Modeler
Kubernetes
Medical LLM
Occubee
Quorso
RazorThink
Tabular
TeamStation
Timbr.ai
Yandex Data Proc
eQube®-DaaS
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