DBMS > OpenMLDB vs. RDF4J vs. Titan

System Properties Comparison OpenMLDB vs. RDF4J vs. Titan

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Editorial information provided by DB-Engines

Name

Titan has been decommisioned after the takeover by Datastax. It will be removed from the DB-Engines ranking. A fork has been open-sourced as JanusGraph.

Description

An open-source machine learning database that provides a feature platform for training and inference

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

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Time Series DBMS

RDF store

Graph DBMS

Secondary database models

Relational DBMS

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

Score	0.11
Rank	#339	Overall
	#30	Time Series DBMS

Score	0.72
Rank	#222	Overall
	#9	RDF stores

Website

openmldb.ai

rdf4j.org

github.com/thinkaurelius/titan

Technical documentation

openmldb.ai/docs/zh/main

rdf4j.org/documentation

github.com/thinkaurelius/titan/wiki

Developer

4 Paradigm Inc.

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

Aurelius, owned by DataStax

Initial release

2020

2004

2012

Current release

2024-2 February 2024

License

Commercial or Open Source

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

Apache license, version 2.0

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C++, Java, Scala

Java

Server operating systems

Linux

Linux
OS X
Unix
Windows

Data scheme

Fixed schema

yes

RDF Schemas

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.

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

JDBC
SQLAlchemy

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

C++
Go
Java
Python
Scala

Java
PHP
Python

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via Faunus, a graph analytics engine

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

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

in-memory storage is supported as well

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

In-memory capabilities

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

yes

User concepts

Access control

fine grained access rights according to SQL-standard

User authentification and security via Rexster Graph Server

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More resources

DB-Engines blog posts

Graph DBMS increased their popularity by 500% within the last 2 years
3 March 2015, Paul Andlinger

Graph DBMSs are gaining in popularity faster than any other database category
21 January 2014, Matthias Gelbmann

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Recent citations in the news

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