DBMS > AnzoGraph DB vs. GraphDB vs. Microsoft Azure Cosmos DB

System Properties Comparison AnzoGraph DB vs. GraphDB vs. Microsoft Azure Cosmos DB

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Editorial information provided by DB-Engines

Name

Description

Scalable graph database built for online analytics and data harmonization with MPP scaling, high-performance analytical algorithms and reasoning, and virtualization

Enterprise-ready RDF and graph database with efficient reasoning, cluster and external index synchronization support. It supports also SQL JDBC access to Knowledge Graph and GraphQL over SPARQL.

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Graph DBMS
RDF store

Document store
Graph DBMS
Key-value store
Wide column store

Secondary database models

Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	0.21
Rank	#308	Overall
	#25	Graph DBMS
	#15	RDF stores

Score	2.59
Rank	#96	Overall
	#7	Graph DBMS
	#3	RDF stores

Score	22.94
Rank	#26	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#2	Wide column stores

Website

cambridgesemantics.com/anzograph

www.ontotext.com

azure.microsoft.com/services/cosmos-db

Technical documentation

docs.cambridgesemantics.com/anzograph/userdoc/home.htm

graphdb.ontotext.com/documentation

learn.microsoft.com/azure/cosmos-db

Developer

Cambridge Semantics

Ontotext

Microsoft

Initial release

2018

2000

2014

Current release

2.3, January 2021

10.4, October 2023

License

Commercial or Open Source

commercial

free trial version available

commercial

Some plugins of GraphDB Workbench are open sourced

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Server operating systems

Linux

All OS with a Java VM
Linux
OS X
Windows

hosted

Data scheme

Schema-free and OWL/RDFS-schema support

schema-free and OWL/RDFS-schema support; RDF shapes

schema-free

Typing

predefined data types such as float or date

yes

JSON types

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

Secondary indexes

yes, supports real-time synchronization and indexing in SOLR/Elastic search/Lucene and GeoSPARQL geometry data indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

SPARQL and SPARQL* as primary query language. Cypher preview.

stored SPARQL accessed as SQL using Apache Calcite through JDBC/ODBC

SQL-like query language

APIs and other access methods

Apache Mule
gRPC
JDBC
Kafka
OData access for BI tools
OpenCypher
RESTful HTTP API
SPARQL

GeoSPARQL
GraphQL
GraphQL Federation
Java API
JDBC
RDF4J API
RDFS
RIO
Sail API
Sesame REST HTTP Protocol
SPARQL 1.1

DocumentDB API
Graph API (Gremlin)
MongoDB API
RESTful HTTP API
Table API

Supported programming languages

C++
Java
Python

.Net
C#
Clojure
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

.Net
C#
Java
JavaScript
JavaScript (Node.js)
MongoDB client drivers written for various programming languages
Python

Server-side scripts

Stored procedures

user defined functions and aggregates

well-defined plugin interfaces; JavaScript server-side extensibility

JavaScript

Triggers

JavaScript

Partitioning methods

Methods for storing different data on different nodes

Automatic sharding

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in MPP-Cluster

Multi-source replication

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

Kerberos/HDFS data loading

with Hadoop integration

Integration with Hadoop/HDInsight on Azure*

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency in MPP-Cluster

Immediate Consistency, Eventual consistency (configurable in cluster mode per master or individual client request)

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

not needed in graphs

yes

Constraint checking

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Multi-item ACID transactions with snapshot isolation within a partition

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

Access rights for users and roles

Default Basic authentication through RDF4J client, or via Java when run with cURL, default token-based in the Workbench or via Rest API, optional access through OpenID or Kerberos single sign-on.

Access rights can be defined down to the item level

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More resources

Recent citations in the news

AnzoGraph review: A graph database for deep analytics
15 April 2019, InfoWorld

Cambridge Semantics Fits AnzoGraph DB with More Speed, Free Access
23 January 2020, solutionsreview.com

How Knowledge Graphs Automate Data Preparation
15 July 2020, Database Trends and Applications

The 12 Best Graph Databases to Consider for 2025
1 January 2025, solutionsreview.com

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Semantic Web Company and Ontotext merge to form Graphwise
23 October 2024, Blocks and Files

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23 October 2024, PR Newswire

Ontotext Platform 3.0 for Enterprise Knowledge Graphs Released
18 December 2019, KDnuggets

Ontotext's GraphDB 9.2 Supports RDF* to Match the Expressivity of Property Graphs
30 April 2020, PR Newswire UK

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5 July 2022, PR Newswire

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