DBMS > Axibase vs. BigObject vs. EventStoreDB vs. Sequoiadb vs. Titan

System Properties Comparison Axibase vs. BigObject vs. EventStoreDB vs. Sequoiadb vs. Titan

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

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

Analytic DBMS for real-time computations and queries

Industrial-strength, open-source database solution built from the ground up for event sourcing.

NewSQL database with distributed OLTP and SQL

Titan is a Graph DBMS optimized for distributed clusters.

Primary database model

Time Series DBMS

Relational DBMS

a hierachical model (tree) can be imposed

Event Store

Document store
Relational DBMS

Graph DBMS

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

Score	0.29
Rank	#292	Overall
	#25	Time Series DBMS

Score	0.13
Rank	#333	Overall
	#147	Relational DBMS

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

axibase.com/docs/atsd/finance

bigobject.io

www.eventstore.com

www.sequoiadb.com

github.com/thinkaurelius/titan

Technical documentation

docs.bigobject.io

developers.eventstore.com

www.sequoiadb.com/en/index.php?m=Files&a=index

github.com/thinkaurelius/titan/wiki

Developer

Axibase Corporation

BigObject, Inc.

Event Store Limited

Sequoiadb Ltd.

Aurelius, owned by DataStax

Initial release

2013

2015

2012

2013

2012

Current release

15585

21.2, February 2021

License

Commercial or Open Source

commercial

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

commercial

free community edition available

Open Source

Server: AGPL; Client: Apache V2

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

Java

C++

Java

Server operating systems

Linux

distributed as a docker-image
OS X

distributed as a docker-image (boot2docker)
Windows

distributed as a docker-image (boot2docker)

Linux
Windows

Linux

Linux
OS X
Unix
Windows

Data scheme

yes

schema-free

yes

Typing

predefined data types such as float or date

yes

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

yes

oid, date, timestamp, binary, regex

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

SQL-like DML and DDL statements

SQL-like query language

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

fluentd
ODBC
RESTful HTTP API

proprietary protocol using JSON

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

Supported programming languages

Go
Java
PHP
Python
R
Ruby

.Net
C++
Java
PHP
Python

Clojure
Java
Python

Server-side scripts

Stored procedures

yes

Lua

JavaScript

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

yes

via pluggable storage backends

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

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

none

Eventual Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

automatically between fact table and dimension tables

yes

Relationships in graph

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

Document is locked during a transaction

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/write lock on objects (tables, trees)

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

User concepts

Access control

simple password-based access control

User authentification and security via Rexster Graph Server

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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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