AnzoGraph DB

AnzoGraph DB

Cambridge Semantics
Graph Engine

Graph Engine

Microsoft

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

Blazegraph™ DB is a ultra high-performance graph database supporting Blueprints and RDF/SPARQL APIs. It supports up to 50 Billion edges on a single machine. It is in production use for Fortune 500 customers such as EMC, Autodesk, and many others. It is supporting key Precision Medicine applications and has wide-spread usage for life science applications. It is used extensively to support Cyber analytics in commercial and government applications. It powers the Wikimedia Foundation's Wikidata Query Service. You can choose an executable jar, war file, or tar.gz distribution. Blazegraph is designed to be easy to use and get started. It ships without SSL or authentication by default for this reason. For production deployments, we strongly recommend you enable SSL, authentication, and appropriate network configurations. There are some helpful links below to enable you to do this.

About

Graph Engine (GE) is a distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine. The distributed RAM store provides a globally addressable high-performance key-value store over a cluster of machines. Through the RAM store, GE enables the fast random data access power over a large distributed data set. The capability of fast data exploration and distributed parallel computing makes GE a natural large graph processing platform. GE supports both low-latency online query processing and high-throughput offline analytics on billion-node large graphs. Schema does matter when we need to process data efficiently. Strongly-typed data modeling is crucial for compact data storage, fast data access, and clear data semantics. GE is good at managing billions of run-time objects of varied sizes. One byte counts as the number of objects goes large. GE provides fast memory allocation and reallocation with high memory ratios.

About

The JavaScript InfoVis Toolkit provides tools for creating interactive data visualizations for the web. The best way to start is to take a look at the demos page. Each demo has a See the Example Code link that takes you to the code for that example. The actual library code is included in the HTML file by building the lib each time with only the needed requirements taken from the name of the visualization and the build.json file. The required library code is built by the build.py file. In order to create a new visualization you need to set up the server environment to include test JavaScript files for your new visualization and also you need to add the new visualization files into the Source folder.

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 looking for a high-performance graph database software solution

Audience

Companies and developers looking for a distributed in-memory data processing engine solution

Audience

Developers in need of a tool for creating interactive data visualizations for the web

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

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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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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

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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

Blazegraph
Founded: 2006
United States
blazegraph.com

Company Information

Microsoft
Founded: 1975
United States
www.graphengine.io

Company Information

SenchaLabs
Founded: 2013
United States
philogb.github.io/jit/

Alternatives

Alternatives

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Cambridge Semantics

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OrigoDB

OrigoDB

Origo

Categories

Categories

Categories

Categories

Integrations

Amazon Web Services (AWS)
Apache Kafka
Docker
Google Cloud Platform
Jupyter Notebook
Microsoft Azure
Red Hat Cloud Suite
Tableau
Wink

Integrations

Amazon Web Services (AWS)
Apache Kafka
Docker
Google Cloud Platform
Jupyter Notebook
Microsoft Azure
Red Hat Cloud Suite
Tableau
Wink

Integrations

Amazon Web Services (AWS)
Apache Kafka
Docker
Google Cloud Platform
Jupyter Notebook
Microsoft Azure
Red Hat Cloud Suite
Tableau
Wink

Integrations

Amazon Web Services (AWS)
Apache Kafka
Docker
Google Cloud Platform
Jupyter Notebook
Microsoft Azure
Red Hat Cloud Suite
Tableau
Wink
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