DBMS > DataFS vs. Drizzle vs. Sadas Engine vs. Titan

System Properties Comparison DataFS vs. Drizzle vs. Sadas Engine vs. Titan

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Editorial information provided by DB-Engines

Name

Drizzle has published its last release in September 2012. The open-source project is discontinued and Drizzle is excluded from the DB-Engines ranking.

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

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

MySQL fork with a pluggable micro-kernel and with an emphasis of performance over compatibility.

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Object oriented DBMS

Relational DBMS

Graph DBMS

Secondary database models

Graph DBMS

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

Score	0.02
Rank	#369	Overall
	#18	Object oriented DBMS

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Website

newdatabase.com

www.sadasengine.com

github.com/thinkaurelius/titan

Technical documentation

dev.mobiland.com/Overview.xsp

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

github.com/thinkaurelius/titan/wiki

Developer

Mobiland AG

Drizzle project, originally started by Brian Aker

SADAS s.r.l.

Aurelius, owned by DataStax

Initial release

2018

2008

2006

2012

Current release

1.1.263, October 2022

7.2.4, September 2012

8.0

License

Commercial or Open Source

commercial

Open Source

GNU GPL

commercial

free trial version available

Open Source

Apache license, version 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

C++

Java

Server operating systems

Windows

FreeBSD
Linux
OS X

AIX
Linux
Windows

Linux
OS X
Unix
Windows

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

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

with proprietary extensions

yes

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

JDBC

JDBC
ODBC
Proprietary protocol

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

.Net
C
C#
C++
VB.Net

C
C++
Java
PHP

.Net
C
C#
C++
Groovy
Java
PHP
Python

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

Triggers

no, except callback-events from server when changes happened

hooks for callbacks inside the server can be used.

yes

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

Sharding

horizontal partitioning

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

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

managed by 'Learn by Usage'

User concepts

Access control

Windows-Profile

Pluggable authentication mechanisms

e.g. LDAP, HTTP

Access rights for users, groups and roles according to SQL-standard

User authentification and security via Rexster Graph Server

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More resources

DB-Engines blog posts

MySQL won the April ranking; did its forks follow?
1 April 2015, Paul Andlinger

Has MySQL finally lost its mojo?
1 July 2013, Matthias Gelbmann

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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

DataStax Acquires Aurelius and its TitanDB Graph Database
31 May 2024, Data Center Knowledge

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
24 August 2015, AWS Blog

DataStax acquires Aurelius, the startup behind the Titan graph database
3 February 2015, VentureBeat

Beyond Titan: The Evolution of DataStax’s New Graph Database
21 June 2016, Datanami

provided by Google News

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