DBMS > AllegroGraph vs. Citus vs. Microsoft Azure Cosmos DB

System Properties Comparison AllegroGraph vs. Citus vs. Microsoft Azure Cosmos DB

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Editorial information provided by DB-Engines

Name

Description

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

Scalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQL

Globally distributed, horizontally scalable, multi-model database service

Primary database model

Document store

with version 6.5
Graph DBMS
RDF store

Relational DBMS

Document store
Graph DBMS
Key-value store
Spatial DBMS
Wide column store

Secondary database models

Spatial DBMS

Document store

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

Score	1.31
Rank	#147	Overall
	#25	Document stores
	#12	Graph DBMS
	#7	RDF stores

Score	1.36
Rank	#143	Overall
	#72	Relational DBMS

Score	32.41
Rank	#25	Overall
	#3	Document stores
	#2	Graph DBMS
	#3	Key-value stores
	#1	Spatial DBMS
	#3	Wide column stores

Website

allegrograph.com

www.citusdata.com

azure.microsoft.com/services/cosmos-db

Technical documentation

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

docs.citusdata.com

docs.microsoft.com/azure/cosmos-db

Developer

Franz Inc.

Microsoft

Initial release

2004

2010

2014

Current release

7.0.0, April 2020

8.1, December 2018

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

AGPL, commercial license also 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.

Implementation language

Server operating systems

Linux
OS X
Windows

Linux

hosted

Data scheme

yes

RDF schemas

yes

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.

bulk load of XML files possible

yes

specific XML type available, but no XML query functionality

Secondary indexes

yes

All properties auto-indexed by default

SQL

Support of SQL

SPARQL is used as query language

yes

standard, with numerous extensions

SQL-like query language

APIs and other access methods

RESTful HTTP API
SPARQL

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

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

Supported programming languages

C#
Clojure
Java
Lisp
Perl
Python
Ruby
Scala

.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

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

Server-side scripts

Stored procedures

yes

JavaScript or Common Lisp

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

JavaScript

Triggers

yes

JavaScript

Partitioning methods

Methods for storing different data on different nodes

with Federation

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

other methods possible by using 3rd party extensions

yes

Implicit feature of the cloud service

MapReduce

Offers an API for user-defined Map/Reduce methods

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

Bounded Staleness
Consistent Prefix
Eventual Consistency
Immediate Consistency

Consistency level configurable on request level
Session Consistency

Foreign keys

Referential integrity

yes

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.

User concepts

Access control

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

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

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

Data-Centric Architecture Forum – DCAF 2021
1 February 2021

Data Fabrics and Knowledge Graphs — A Symbiotic Relationship
6 November 2020

RDF vs Property Graph – The Graph Show
3 November 2020

Text Analytics Forum 2020 – KMWorld Connect
27 October 2020

Sharing Ontologies Globally To Speed Science And Healthcare Solutions – OntoPortal
7 October 2020

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