DBMS > Hypertable vs. TimesTen vs. Titan vs. Yaacomo vs. Yanza

System Properties Comparison Hypertable vs. TimesTen vs. Titan vs. Yaacomo vs. Yanza

Editorial information provided by DB-Engines

Name

Hypertable has stopped its further development with March 2016 and is removed 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.

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.

Description

An open source BigTable implementation based on distributed file systems such as Hadoop

In-Memory RDBMS compatible to Oracle

Titan is a Graph DBMS optimized for distributed clusters.

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Time Series DBMS for IoT Applications

Primary database model

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

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

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

github.com/thinkaurelius/titan

yaacomo.com

yanza.com

Technical documentation

docs.oracle.com/database/timesten-18.1

github.com/thinkaurelius/titan/wiki

Developer

Hypertable Inc.

Oracle, TimesTen Performance Software, HP

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

Aurelius, owned by DataStax

Q2WEB GmbH

Yanza

Initial release

2009

1998

2012

2009

2015

Current release

0.9.8.11, March 2016

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

GNU version 3. Commercial license available

commercial

Open Source

Apache license, version 2.0

commercial

free version available

Cloud-based only

Only available as a cloud service

but mainly used as a service provided by Yanza

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

Linux
OS X
Windows

an inofficial Windows port is available

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

Linux
OS X
Unix
Windows

Android
Linux
Windows

Windows

Data scheme

schema-free

yes

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.

Secondary indexes

restricted

only exact value or prefix value scans

yes

SQL

Support of SQL

yes

APIs and other access methods

C++ API
Thrift

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JDBC
ODBC

HTTP API

Supported programming languages

C++
Java
Perl
PHP
Python
Ruby

C
C++
Java
PL/SQL

Clojure
Java
Python

any language that supports HTTP calls

Server-side scripts

Stored procedures

PL/SQL

yes

Triggers

yes

Timer and event based

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

yes

via pluggable storage backends

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor on file system level

Multi-source replication
Source-replica replication

yes

Source-replica replication

none

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

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Relationships in graph

yes

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

fine grained access rights according to SQL-standard

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

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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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