DBMS > Datomic vs. RDF4J vs. Riak TS vs. Stardog vs. TinkerGraph

System Properties Comparison Datomic vs. RDF4J vs. Riak TS vs. Stardog vs. TinkerGraph

Editorial information provided by DB-Engines

Name

Description

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

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

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

A lightweight, in-memory graph engine that serves as a reference implementation of the TinkerPop3 API

Primary database model

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

Score	1.55
Rank	#144	Overall
	#67	Relational DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Score	0.17
Rank	#318	Overall
	#27	Time Series DBMS

Score	1.93
Rank	#121	Overall
	#10	Graph DBMS
	#6	RDF stores

Score	0.08
Rank	#345	Overall
	#34	Graph DBMS

Website

www.datomic.com

rdf4j.org

www.stardog.com

tinkerpop.apache.org/docs/current/reference/#tinkergraph-gremlin

Technical documentation

docs.datomic.com

rdf4j.org/documentation

www.tiot.jp/riak-docs/riak/ts/latest

docs.stardog.com

Developer

Cognitect

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

Open Source, formerly Basho Technologies

Stardog-Union

Initial release

2012

2004

2015

2010

2009

Current release

1.0.7180, July 2024

3.0.0, September 2022

7.3.0, May 2020

License

Commercial or Open Source

commercial

limited edition free

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

Apache 2.0

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

Erlang

Java

Server operating systems

All OS with a Java VM

Linux
OS X
Unix
Windows

Linux
OS X

Linux
macOS
Windows

Data scheme

yes

RDF Schemas

schema-free

schema-free and OWL/RDFS-schema support

schema-free

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.

Import/export of XML data possible

Secondary indexes

yes

restricted

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes, limited

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP API
Native Erlang Interface

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

TinkerPop 3

Supported programming languages

Clojure
Java

Java
PHP
Python

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Groovy
Java

Server-side scripts

Stored procedures

yes

Transaction Functions

yes

Erlang

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

By using transaction functions

yes

pre-commit hooks and post-commit hooks

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

none

But extensive use of caching in the application peers

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

But extensive use of caching in the application peers

none

selectable replication factor

Multi-source replication in HA-Cluster

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency in HA-Cluster

none

Foreign keys

Referential integrity

links between datasets can be stored

yes

relationships in graphs

yes

Relationships in graphs

Transaction concepts

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

ACID

Isolation support depends on the API used

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 storage is supported as well

yes

optional

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

Access rights for users and roles

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