DBMS > Citus vs. Datomic vs. HBase vs. RDF4J

System Properties Comparison Citus vs. Datomic vs. HBase vs. RDF4J

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Editorial information provided by DB-Engines

Name

Description

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

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

Wide-column store based on Apache Hadoop and on concepts of BigTable

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Relational DBMS

Wide column store

RDF store

Secondary database models

Document store

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

Score	2.21
Rank	#118	Overall
	#56	Relational DBMS

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

Technical documentation

docs.citusdata.com

docs.datomic.com

hbase.apache.org/book.html

rdf4j.org/documentation

Developer

Cognitect

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2010

2012

2008

2004

Current release

8.1, December 2018

1.0.6735, June 2023

2.3.4, January 2021

License

Commercial or Open Source

Open Source

AGPL, commercial license also available

commercial

limited edition free

Open Source

Apache version 2

Open Source

Eclipse Distribution License (EDL), v1.0.

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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

Implementation language

Java, Clojure

Java

Server operating systems

Linux

All OS with a Java VM

Linux
Unix
Windows

using Cygwin

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free, schema definition possible

yes

RDF Schemas

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

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

RESTful HTTP API

Java API
RESTful HTTP API
Thrift

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

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

Clojure
Java

C
C#
C++
Groovy
Java
PHP
Python
Scala

Java
PHP
Python

Server-side scripts

Stored procedures

user defined functions

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

yes

Transaction Functions

yes

Coprocessors in Java

yes

Triggers

yes

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

But extensive use of caching in the application peers

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

none

But extensive use of caching in the application peers

Multi-source replication
Source-replica replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Single row ACID (across millions of columns)

ACID

Isolation support depends on the API used

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 storage is supported as well

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

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