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What is AnzoGraph DB?

AnzoGraph DB offers an extensive suite of analytical tools that can greatly enhance your analytical framework. This video demonstrates how AnzoGraph DB operates as a native graph database with Massively Parallel Processing (MPP) capabilities, specifically engineered for data integration and analysis. It is designed for horizontal scalability, making it ideal for online analytical processes and addressing the challenges associated with data integration. Address the intricacies of linked data and data integration with AnzoGraph DB, a prominent contender in the analytical graph database sector. The platform provides strong online performance, making it well-suited for large-scale enterprise graph applications. AnzoGraph DB is compatible with well-known semantic graph languages such as SPARQL*/OWL, and it also supports Labeled Property Graphs (LPGs). With access to a wide array of analytical, machine learning, and data science capabilities, users can uncover insights with unparalleled speed and scale. Additionally, it emphasizes the importance of context and relationships among data points during analysis, featuring extremely fast data loading and quick execution of analytical queries. This unique combination of features establishes AnzoGraph DB as an indispensable resource for organizations aiming to maximize the effectiveness of their data usage, allowing businesses to stay ahead in an increasingly data-driven world.

What is AllegroGraph?

AllegroGraph stands out as a groundbreaking solution that facilitates limitless data integration, employing a proprietary method to consolidate fragmented data and information into an Entity Event Knowledge Graph framework designed for extensive big data analysis. By leveraging its distinctive federated sharding features, AllegroGraph delivers comprehensive insights and supports intricate reasoning over a distributed Knowledge Graph. Additionally, users of AllegroGraph can access an integrated version of Gruff, an intuitive browser-based tool for graph visualization that aids in uncovering and understanding relationships within enterprise Knowledge Graphs. Moreover, Franz's Knowledge Graph Solution not only encompasses advanced technology but also offers services aimed at constructing robust Entity Event Knowledge Graphs, drawing upon top-tier products, tools, expertise, and experience in the field. This comprehensive approach ensures that organizations can effectively harness their data for strategic decision-making and innovation.

Media

Media

Integrations Supported

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

Integrations Supported

Docker
Apache Solr
Cloudera
Hackolade
Kubernetes
MongoDB
PoolParty
Swarm

API Availability

API Availability

Has API

Pricing Information

Pricing not provided

Pricing Information

Pricing not provided
Free Version
Free Trial Offered?

Supported Platforms

SaaS

Supported Platforms

SaaS
Windows
Mac

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Customer Service / Support

Standard Support
24 Hour Support
Web-Based Support

Training Options

Documentation Hub
Webinars
Online Training

Training Options

Documentation Hub
Webinars
Online Training
On-Site Training

Company Facts

Organization Name

Cambridge Semantics

Date Founded

2007

Company Location

United States

Company Website

www.cambridgesemantics.com/anzograph/

Company Facts

Organization Name

Franz Inc.

Company Location

San Francisco Bay Area

Company Website

www.franz.com

Categories and Features

Graph Databases

Not specified

Categories and Features

Data Visualization

Not specified

Database

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

Distributed Databases

Not specified

Graph Databases

Not specified

Graphing

Not specified

Knowledge Management

Not specified

Machine Learning

Not specified

NoSQL Database

Auto-sharding
Automatic Database Replication
Data Model Flexibility
Deployment Flexibility
Dynamic Schemas
Integrated Caching
Multi-Model
Performance Management
Security Management

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