DBMS > CouchDB vs. EJDB vs. Graph Engine vs. HyperSQL vs. SQLite

System Properties Comparison CouchDB vs. EJDB vs. Graph Engine vs. HyperSQL vs. SQLite

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)

A distributed in-memory data processing engine, underpinned by a strongly-typed RAM store and a general distributed computation engine

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

Widely used embeddable, in-process RDBMS

Primary database model

Document store

Graph DBMS
Key-value 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	9.30
Rank	#45	Overall
	#7	Document stores

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.61
Rank	#240	Overall
	#21	Graph DBMS
	#35	Key-value stores

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

couchdb.apache.org

github.com/Softmotions/ejdb

www.graphengine.io

hsqldb.org

www.sqlite.org

Technical documentation

docs.couchdb.org/en/stable

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

www.graphengine.io/docs/manual

hsqldb.org/web/hsqlDocsFrame.html

www.sqlite.org/docs.html

Developer

Apache Software Foundation

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

Softmotions

Microsoft

Dwayne Richard Hipp

Initial release

2005

2012

2010

2001

2000

Current release

3.3.3, December 2023

2.7.2, June 2023

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

Open Source

Apache version 2

Open Source

GPLv2

Open Source

MIT License

Open Source

based on BSD license

Open Source

Public Domain

Cloud-based only

Only available as a cloud service

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Implementation language

Erlang

.NET and C

Java

Server operating systems

Android
BSD
Linux
OS X
Solaris
Windows

server-less

.NET

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

server-less

Data scheme

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

string, integer, double, bool, date, object_id

yes

not rigid because of 'dynamic typing' concept.

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

SQL-92 is not fully supported

APIs and other access methods

RESTful HTTP/JSON API

in-process shared library

RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

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++
F#
Visual Basic

All languages supporting JDBC/ODBC
Java

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

View functions in JavaScript

yes

Java, SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

improved architecture with release 2.0

none

horizontal partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

none

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

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

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

Read/Write Locking

yes

via file-system locks

Durability

Support for making data persistent

yes

optional: either by committing a write-ahead log (WAL) to the local persistent storage or by dumping the memory to a persistent storage

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

Access rights for users can be defined per database

fine grained access rights according to SQL-standard

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