AnzoGraph DB

AnzoGraph DB

Cambridge Semantics
GraphDB

GraphDB

Ontotext
GraphBase

GraphBase

FactNexus

About

With a huge collection of analytical features, AnzoGraph DB can enhance your analytical framework. Watch this video to learn how AnzoGraph DB is a Massively Parallel Processing (MPP) native graph database that is built for data harmonization and analytics. Horizontally scalable graph database built for online analytics and data harmonization. Take on data harmonization and linked data challenges with AnzoGraph DB, a market-leading analytical graph database. AnzoGraph DB provides industrialized online performance for enterprise-scale graph applications. AnzoGraph DB uses familiar SPARQL*/OWL for semantic graphs but also supports Labeled Property Graphs (LPGs). Access to many analytical, machine learning and data science capabilities help you achieve new insights, delivered at unparalleled speed and scale. Use context and relationships between data as first-class citizens in your analysis. Ultra-fast data loading and analytical queries.

About

*GraphDB allows you to link diverse data, index it for semantic search and enrich it via text analysis to build big knowledge graphs.* GraphDB is a highly efficient and robust graph database with RDF and SPARQL support. The GraphDB database supports a highly available replication cluster, which has been proven in a number of enterprise use cases that required resilience in data loading and query answering. If you need a quick overview of GraphDB or a download link to its latest releases, please visit the GraphDB product section. GraphDB uses RDF4J as a library, utilizing its APIs for storage and querying, as well as the support for a wide variety of query languages (e.g., SPARQL and SeRQL) and RDF syntaxes (e.g., RDF/XML, N3, Turtle).

About

GraphBase is a Graph Database Management System (Graph DBMS) engineered to simplify the creation and maintenance of complex data graphs. Complex and highly-connected structures are a challenge for the Relational Database Management System (RDBMS). A graph database provides much better modelling utility, performance and scalability. The current crop of graph database products - the triplestores and property graphs - have been around for nearly two decades. They're powerful tools, they have many uses, but they're still not suited to the management of complex data structures. With GraphBase, our goal was to simplify the management of complex data structures, so that your data could become something more. It could become Knowledge. We achieved this by redefining how graph data should be managed. In GraphBase, the graph is a first-class citizen. You get a graph equivalent of the "rows and tables" paradigm that makes a Relational Database so easy to use.

About

Simple, fast, safe, and compiled. For developing maintainable software. Simple language for building maintainable programs. You can learn the entire language by going through the documentation over a weekend, and in most cases, there's only one way to do something. This results in simple, readable, and maintainable code. This results in simple, readable, and maintainable code. Despite being simple, V gives a lot of power to the developer and can be used in pretty much every field, including systems programming, webdev, gamedev, GUI, mobile, science, embedded, tooling, etc. V is very similar to Go. If you know Go, you already know 80% of V. Bounds checking, No undefined values, no variable shadowing, immutable variables by default, immutable structs by default, option/result and mandatory error checks, sum types, generics, and immutable function args by default, mutable args have to be marked on call.

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

Platforms Supported

Windows
Mac
Linux
Cloud
On-Premises
iPhone
iPad
Android
Chromebook

Audience

Industries that need an horizontally scalable graph database for online analytics and data harmonization

Audience

Developers, Knowledge Managers, Solution Architects, Data Scientists

Audience

Companies and developers interested in a graph database management system solution optimize the creation and maintenance of complex data graphs

Audience

Developers interested in a language for building maintainable programs

Support

Phone Support
24/7 Live Support
Online

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

API

Offers API

Screenshots and Videos

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

No information available.
Free Version
Free Trial

Pricing

Free
Free Version
Free Trial

Reviews/Ratings

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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

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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

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Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Training

Documentation
Webinars
Live Online
In Person

Company Information

Cambridge Semantics
Founded: 2007
United States
www.cambridgesemantics.com/anzograph/

Company Information

Ontotext
Founded: 2008
Bulgaria
www.ontotext.com/product/graphdb

Company Information

FactNexus
Founded: 2010
Australia
graphbase.ai/

Company Information

V Programming Language
United States
vlang.io

Alternatives

Alternatives

AnzoGraph DB

AnzoGraph DB

Cambridge Semantics

Alternatives

Alternatives

Swift

Swift

Apple
InfiniteGraph

InfiniteGraph

Objectivity
GraphBase

GraphBase

FactNexus
Dgraph

Dgraph

Hypermode
GraphDB

GraphDB

Ontotext
Zig

Zig

Zig Software Foundation

Categories

Categories

Categories

Categories

Big Data Features

Collaboration
Data Blends
Data Cleansing
Data Mining
Data Visualization
Data Warehousing
High Volume Processing
No-Code Sandbox
Predictive Analytics
Templates

Database Features

Backup and Recovery
Creation / Development
Data Migration
Data Replication
Data Search
Data Security
Database Conversion
Mobile Access
Monitoring
NOSQL
Performance Analysis
Queries
Relational Interface
Virtualization

Integrations

Amazon Web Services (AWS)
Apache Kafka
Azure Marketplace
C
Docker
Gate
Google Cloud Platform
Hackolade
Helix Editor
JavaScript
Jupyter Notebook
Lapce
Microsoft Azure
MongoDB
Red Hat Cloud Suite
SolrCommerce
Tableau

Integrations

Amazon Web Services (AWS)
Apache Kafka
Azure Marketplace
C
Docker
Gate
Google Cloud Platform
Hackolade
Helix Editor
JavaScript
Jupyter Notebook
Lapce
Microsoft Azure
MongoDB
Red Hat Cloud Suite
SolrCommerce
Tableau

Integrations

Amazon Web Services (AWS)
Apache Kafka
Azure Marketplace
C
Docker
Gate
Google Cloud Platform
Hackolade
Helix Editor
JavaScript
Jupyter Notebook
Lapce
Microsoft Azure
MongoDB
Red Hat Cloud Suite
SolrCommerce
Tableau

Integrations

Amazon Web Services (AWS)
Apache Kafka
Azure Marketplace
C
Docker
Gate
Google Cloud Platform
Hackolade
Helix Editor
JavaScript
Jupyter Notebook
Lapce
Microsoft Azure
MongoDB
Red Hat Cloud Suite
SolrCommerce
Tableau
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