DBMS > Stardog vs. TimesTen vs. Titan vs. VelocityDB

System Properties Comparison Stardog vs. TimesTen vs. Titan vs. VelocityDB

Please select another system to include it in the comparison.

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

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

In-Memory RDBMS compatible to Oracle

Titan is a Graph DBMS optimized for distributed clusters.

A .NET Object Database that can be embedded/distributed and extended to a graph data model (VelocityGraph)

Primary database model

Graph DBMS
RDF store

Relational DBMS

Graph DBMS

Graph DBMS
Object oriented DBMS

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

Score	2.07
Rank	#122	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Score	0.11
Rank	#354	Overall
	#37	Graph DBMS
	#15	Object oriented DBMS

Website

www.stardog.com

www.oracle.com/database/technologies/related/timesten.html

github.com/thinkaurelius/titan

velocitydb.com

Technical documentation

docs.stardog.com

docs.oracle.com/database/timesten-18.1

github.com/thinkaurelius/titan/wiki

velocitydb.com/UserGuide

Developer

Stardog-Union

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Aurelius, owned by DataStax

VelocityDB Inc

Initial release

2010

1998

2012

2011

Current release

7.3.0, May 2020

11 Release 2 (11.2.2.8.0)

7.x

License

Commercial or Open Source

commercial

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

commercial

Open Source

Apache license, version 2.0

commercial

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

Server operating systems

Linux
macOS
Windows

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

Linux
OS X
Unix
Windows

Any that supports .NET

Data scheme

schema-free and OWL/RDFS-schema support

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.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

yes

SQL

Support of SQL

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

yes

APIs and other access methods

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

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

.Net

Supported programming languages

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C
C++
Java
PL/SQL

Clojure
Java
Python

.Net

Server-side scripts

Stored procedures

user defined functions and aggregates, HTTP Server extensions in Java

PL/SQL

yes

Triggers

yes

via event handlers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

none

yes

via pluggable storage backends

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication in HA-Cluster

Multi-source replication
Source-replica replication

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 in HA-Cluster

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

relationships in graphs

yes

Relationships in graph

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

by means of logfiles and checkpoints

yes

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

yes

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users and roles

fine grained access rights according to SQL-standard

User authentification and security via Rexster Graph Server

Based on Windows Authentication

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

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

show all

Recent citations in the news

Titan Graph Database Integration with DynamoDB: World-class Performance, Availability, and Scale for New Workloads
20 August 2015, All Things Distributed

Amazon DynamoDB Storage Backend for Titan: Distributed Graph Database | Amazon Web Services
24 August 2015, AWS Blog

JanusGraph Picks Up Where TitanDB Left Off
13 January 2017, Datanami

DSE Graph review: Graph database does double duty
14 November 2019, InfoWorld

Database Deep Dives: JanusGraph
8 August 2019, IBM

provided by Google News

Share this page