DBMS > AllegroGraph vs. AnzoGraph DB vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage

System Properties Comparison AllegroGraph vs. AnzoGraph DB vs. Microsoft Azure Cosmos DB vs. Microsoft Azure Table Storage

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Editorial information provided by DB-Engines

Name

Description

High performance, persistent RDF store with additional support for Graph DBMS

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

Globally distributed, horizontally scalable, multi-model database service

A Wide Column Store for rapid development using massive semi-structured datasets

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store
Vector DBMS

Graph DBMS
RDF store

Document store
Graph DBMS
Key-value store
Wide column store

Wide column store

Secondary database models

Spatial DBMS

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

Score	1.13
Rank	#179	Overall
	#30	Document stores
	#17	Graph DBMS
	#7	RDF stores
	#8	Vector DBMS

Score	0.29
Rank	#303	Overall
	#25	Graph DBMS
	#14	RDF stores

Score	27.71
Rank	#27	Overall
	#4	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#3	Wide column stores

Score	4.04
Rank	#77	Overall
	#6	Wide column stores

Website

allegrograph.com

cambridgesemantics.com/anzograph

azure.microsoft.com/services/cosmos-db

azure.microsoft.com/en-us/services/storage/tables

Technical documentation

franz.com/agraph/support/documentation/current/agraph-introduction.html

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

learn.microsoft.com/azure/cosmos-db

Developer

Franz Inc.

Cambridge Semantics

Microsoft

Initial release

2004

2018

2014

2012

Current release

8.0, December 2023

2.3, January 2021

License

Commercial or Open Source

commercial

Limited community edition free

commercial

free trial version available

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.

Server operating systems

Linux
OS X
Windows

Linux

hosted

Data scheme

yes

RDF schemas

Schema-free and OWL/RDFS-schema support

schema-free

Typing

predefined data types such as float or date

yes

JSON types

yes

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.

bulk load of XML files possible

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

SPARQL is used as query language

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

SQL-like query language

APIs and other access methods

RESTful HTTP API
SPARQL

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

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

RESTful HTTP API

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

C++
Java
Python

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

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

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

user defined functions and aggregates

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

with Federation

Automatic sharding

Sharding

Implicit feature of the cloud service

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication in MPP-Cluster

yes

Implicit feature of the cloud service

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

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 or Eventual Consistency depending on configuration

Immediate Consistency in MPP-Cluster

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Immediate Consistency

Foreign keys

Referential integrity

not needed in graphs

Transaction concepts

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

ACID

Multi-item ACID transactions with snapshot isolation within a partition

optimistic locking

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

Users with fine-grained authorization concept, user roles and pluggable authentication

Access rights for users and roles

Access rights can be defined down to the item level

Access rights based on private key authentication or shared access signatures

More information provided by the system vendor

Specific characteristics

Knowledge Graph Platform Leader FedShard - Designed for Entity-Event Knowledge Graph...
» more

Competitive advantages

AllegroGraph is uniquely suited to support adhoc queries through SPARQL, Prolog and...
» more

News

How a Neuro-Symbolic AI Approach Can Improve Trust in AI Apps
23 May 2024

Can Neuro-Symbolic AI Solve AI’s Weaknesses?
17 April 2024

100 Companies That Matter in KM – Franz Inc.
3 April 2024

Exploring AllegroGraph v8 – Unleashing the Power of Neuro-Symbolic AI (Recorded Webinar)
9 February 2024

What is Neuro-Symbolic AI?
23 January 2024

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