DBMS > CouchDB vs. Datomic vs. GBase vs. JanusGraph vs. TimesTen

System Properties Comparison CouchDB vs. Datomic vs. GBase vs. JanusGraph vs. TimesTen

Editorial information provided by DB-Engines

Name

Description

A native JSON - document store inspired by Lotus Notes, scalable from globally distributed server-clusters down to mobile phones.

Datomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durability

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

A Graph DBMS optimized for distributed clusters

It was forked from the latest code base of Titan in January 2017

In-Memory RDBMS compatible to Oracle

Primary database model

Secondary database models

Spatial DBMS

using the Geocouch extension

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

Score	9.30
Rank	#45	Overall
	#7	Document stores

Score	1.59
Rank	#150	Overall
	#69	Relational DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	1.94
Rank	#129	Overall
	#12	Graph DBMS

Score	1.31
Rank	#163	Overall
	#74	Relational DBMS

Website

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

Technical documentation

docs.couchdb.org/en/stable

docs.datomic.com

docs.janusgraph.org

docs.oracle.com/database/timesten-18.1

Developer

Apache Software Foundation

Apache top-level project, originally developed by Damien Katz, a former Lotus Notes developer

Cognitect

General Data Technology Co., Ltd.

Linux Foundation; originally developed as Titan by Aurelius

Oracle, TimesTen Performance Software, HP

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

Initial release

2005

2012

2004

2017

1998

Current release

3.3.3, December 2023

1.0.6735, June 2023

GBase 8a, GBase 8s, GBase 8c

0.6.3, February 2023

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

Apache version 2

commercial

limited edition free

commercial

Open Source

Apache 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

Erlang

Java, Clojure

C, Java, Python

Java

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

All OS with a Java VM

Linux

Linux
OS X
Unix
Windows

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

Data scheme

schema-free

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.

yes

Secondary indexes

yes

via views

yes

SQL

Support of SQL

Standard with numerous extensions

yes

APIs and other access methods

RESTful HTTP/JSON API

RESTful HTTP API

ADO.NET
C API
JDBC
ODBC

Java API
TinkerPop Blueprints
TinkerPop Frames
TinkerPop Gremlin
TinkerPop Rexster

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

C
C#
ColdFusion
Erlang
Haskell
Java
JavaScript
Lisp
Lua
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
Ruby
Smalltalk

Clojure
Java

Clojure
Java
Python

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

View functions in JavaScript

yes

Transaction Functions

user defined functions

yes

PL/SQL

Triggers

yes

By using transaction functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

none

But extensive use of caching in the application peers

horizontal partitioning (by range, list and hash) and vertical partitioning

yes

depending on the used storage backend (e.g. Cassandra, HBase, BerkeleyDB)

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

But extensive use of caching in the application peers

yes

Multi-source replication
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

Eventual Consistency
Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

Relationships in graphs

yes

Transaction concepts

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

atomic operations within a single document possible

ACID

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Durability

Support for making data persistent

yes

using external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)

yes

Supports various storage backends: Cassandra, HBase, Berkeley DB, Akiban, Hazelcast

yes

by means of logfiles and checkpoints

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

recommended only for testing and development

yes

User concepts

Access control

Access rights for users can be defined per database

yes

User authentification and security via Rexster Graph Server

fine grained access rights according to SQL-standard

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