DBMS > Axibase vs. EsgynDB vs. TempoIQ vs. Titan vs. Warp 10

System Properties Comparison Axibase vs. EsgynDB vs. TempoIQ vs. Titan vs. Warp 10

Editorial information provided by DB-Engines

Name

TempoIQ seems to be decommissioned. It will be 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.

Description

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

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Scalable analytics DBMS for sensor data, provided as a service (SaaS)

Titan is a Graph DBMS optimized for distributed clusters.

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

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	0.16
Rank	#329	Overall
	#146	Relational DBMS

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

axibase.com/docs/atsd/finance

www.esgyn.cn

tempoiq.com (offline)

github.com/thinkaurelius/titan

www.warp10.io

Technical documentation

github.com/thinkaurelius/titan/wiki

www.warp10.io/content/02_Getting_started

Developer

Axibase Corporation

Esgyn

TempoIQ

Aurelius, owned by DataStax

SenX

Initial release

2013

2015

2012

2015

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

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C++, Java

Java

Server operating systems

Linux

Linux
OS X
Unix
Windows

Linux
OS X
Windows

Data scheme

yes

schema-free

yes

schema-free

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

ADO.NET
JDBC
ODBC

HTTP API

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

HTTP API
Jupyter
WebSocket

Supported programming languages

Go
Java
PHP
Python
R
Ruby

All languages supporting JDBC/ODBC/ADO.Net

C#
Java
JavaScript

Node.js
Python
Ruby

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

Java Stored Procedures

yes

WarpScript

Triggers

yes

Realtime Alerts

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

via pluggable storage backends

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-source replication between multi datacenters

yes

selectable replication factor

based on HBase

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

Immediate Consistency

based on HBase

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

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

simple authentication-based access control

User authentification and security via Rexster Graph Server

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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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

show all

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