DBMS > AgensGraph vs. Datomic vs. PostgreSQL

System Properties Comparison AgensGraph vs. Datomic vs. PostgreSQL

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Editorial information provided by DB-Engines

Name

Description

Multi-model database supporting relational and graph data models and built upon PostgreSQL

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

Primary database model

Graph DBMS
Relational DBMS

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	0.14
Rank	#331	Overall
	#31	Graph DBMS
	#148	Relational DBMS

Score	1.48
Rank	#143	Overall
	#65	Relational DBMS

Score	667.25
Rank	#4	Overall
	#4	Relational DBMS

Website

bitnine.net/agensgraph

www.datomic.com

www.postgresql.org

Technical documentation

bitnine.net/documentation

docs.datomic.com

www.postgresql.org/docs

Developer

Bitnine Global Inc.

Cognitect

PostgreSQL Global Development Group

www.postgresql.org/developer

Initial release

2016

2012

1989

1989: Postgres, 1996: PostgreSQL

Current release

2.1, December 2018

1.0.7180, July 2024

16.4, August 2024

License

Commercial or Open Source

Open Source

Apache License 2.0

commercial

limited edition free

Open Source

BSD

Cloud-based only

Only available as a cloud service

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Implementation language

Java, Clojure

Server operating systems

Linux
OS X
Windows

All OS with a Java VM

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Data scheme

depending on used data model

yes

Typing

predefined data types such as float or date

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.

yes

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

standard with numerous extensions

APIs and other access methods

Cypher Query Language
JDBC

RESTful HTTP API

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

Supported programming languages

C
Java
JavaScript
Python

Clojure
Java

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

yes

Transaction Functions

user defined functions

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

Triggers

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

no, but can be realized using table inheritance

none

But extensive use of caching in the application peers

partitioning by range, list and (since PostgreSQL 11) by hash

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

But extensive use of caching in the application peers

Source-replica replication

other methods possible by using 3rd party extensions

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

In-memory capabilities

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

yes

recommended only for testing and development

User concepts

Access control

fine grained access rights according to SQL-standard

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