DBMS > CouchDB vs. EJDB vs. TimesTen vs. VoltDB

System Properties Comparison CouchDB vs. EJDB vs. TimesTen vs. VoltDB

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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.

Embeddable document-store database library with JSON representation of queries (in MongoDB style)

In-Memory RDBMS compatible to Oracle

Distributed In-Memory NewSQL RDBMS

Used for OLTP applications with a high frequency of relatively simple transactions, that can hold all their data in memory

Primary database model

Document store

Relational DBMS

Secondary database models

Spatial DBMS

using the Geocouch extension

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

Score	10.26
Rank	#45	Overall
	#7	Document stores

Score	0.30
Rank	#294	Overall
	#44	Document stores

Score	1.35
Rank	#165	Overall
	#75	Relational DBMS

Score	1.46
Rank	#159	Overall
	#74	Relational DBMS

Website

couchdb.apache.org

github.com/Softmotions/ejdb

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

www.voltdb.com

Technical documentation

docs.couchdb.org/en/stable

github.com/Softmotions/ejdb/blob/master/README.md

docs.oracle.com/database/timesten-18.1

docs.voltdb.com

Developer

Apache Software Foundation

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

Softmotions

Oracle, TimesTen Performance Software, HP

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

VoltDB Inc.

Initial release

2005

2012

1998

2010

Current release

3.3.3, December 2023

11 Release 2 (11.2.2.8.0)

11.3, April 2022

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

GPLv2

commercial

Open Source

AGPL for Community Edition, commercial license for Enterprise, AWS, and Pro Editions

Cloud-based only

Only available as a cloud service

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Database as a Service

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Implementation language

Erlang

Java, C++

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

server-less

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

Linux
OS X

for development

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

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

via views

yes

SQL

Support of SQL

yes

only a subset of SQL 99

APIs and other access methods

RESTful HTTP/JSON API

in-process shared library

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Java API
JDBC
RESTful HTTP/JSON API

Supported programming languages

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

Actionscript
C
C#
C++
Go
Java
JavaScript (Node.js)
Lua
Objective-C
Pike
Python
Ruby

C
C++
Java
PL/SQL

C#
C++
Erlang

not officially supported
Go
Java
JavaScript

Node.js
PHP
Python

Server-side scripts

Stored procedures

View functions in JavaScript

PL/SQL

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

yes

FOREIGN KEY constraints are not supported

Transaction concepts

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

atomic operations within a single document possible

ACID

Transactions are executed single-threaded within stored procedures

Concurrency

Support for concurrent manipulation of data

yes

strategy: optimistic locking

yes

Read/Write Locking

yes

Data access is serialized by the server

Durability

Support for making data persistent

yes

by means of logfiles and checkpoints

yes

Snapshots and command logging

In-memory capabilities

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

yes

User concepts

Access control

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

Users and roles with access to stored procedures

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More resources

DB-Engines blog posts

Couchbase climbs up the DB-Engines Ranking, increasing its popularity by 10% every month
2 June 2014, Matthias Gelbmann

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Recent citations in the news

How to install the CouchDB NoSQL database on Debian Server 11
16 June 2022, TechRepublic

IBM Cloudant pulls plan to fund new foundational layer for CouchDB
15 March 2022, The Register

CouchDB 3.0 ends admin party era • DEVCLASS
27 February 2020, DevClass

CouchDB 3.0 puts safety first
27 February 2020, InfoWorld

How to Connect Your Flask App With CouchDB: A NoSQL Database - MUO
14 August 2021, MakeUseOf

provided by Google News

VoltDB Launches Active(N) Lossless Cross Data Center Replication
31 August 2021, PR Newswire

VoltDB Combines Streaming, Global Data
1 February 2017, Datanami

VoltDB Adds Geospatial Support, Cross-Site Replication
28 January 2016, The New Stack

VoltDB Upgrades Power, Security of Its In-Memory Database
1 February 2017, eWeek

VoltDB Aims for Fast Big Data Development -- ADTmag
29 January 2015, ADT Magazine

provided by Google News

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