DBMS > Axibase vs. Netezza vs. Titan vs. Yaacomo

System Properties Comparison Axibase vs. Netezza vs. Titan vs. Yaacomo

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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.

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

Description

Scalable TimeSeries DBMS based on HBase with integrated rule engine and visualization

Data warehouse and analytics appliance part of IBM PureSystems

Titan is a Graph DBMS optimized for distributed clusters.

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

Primary database model

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

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Website

axibase.com/docs/atsd/finance

www.ibm.com/products/netezza

github.com/thinkaurelius/titan

yaacomo.com

Technical documentation

github.com/thinkaurelius/titan/wiki

Developer

Axibase Corporation

IBM

Aurelius, owned by DataStax

Q2WEB GmbH

Initial release

2013

2000

2012

2009

Current release

15585

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

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

included in appliance

Linux
OS X
Unix
Windows

Android
Linux
Windows

Data scheme

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

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

SQL-like query language

yes

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

JDBC
ODBC
OLE DB

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JDBC
ODBC

Supported programming languages

Go
Java
PHP
Python
R
Ruby

C
C++
Fortran
Java
Lua
Perl
Python
R

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

via pluggable storage backends

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Source-replica replication

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

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

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

Users with fine-grained authorization concept

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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