DBMS > EJDB vs. MonetDB vs. openGauss vs. TimesTen

System Properties Comparison EJDB vs. MonetDB vs. openGauss vs. TimesTen

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

A relational database management system that stores data in columns

An enterprise-class RDBMS compatible with high-performance, high-availability and high-performance originally developed by Huawei

In-Memory RDBMS compatible to Oracle

Primary database model

Document store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	0.31
Rank	#296	Overall
	#44	Document stores

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	1.06
Rank	#184	Overall
	#84	Relational DBMS

Score	1.36
Rank	#161	Overall
	#75	Relational DBMS

Website

github.com/Softmotions/ejdb

www.monetdb.org

gitee.com/opengauss
opengauss.org

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

Technical documentation

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

www.monetdb.org/Documentation

docs.opengauss.org/en
gitee.com/opengauss/docs

docs.oracle.com/database/timesten-18.1

Developer

Softmotions

MonetDB BV

Huawei and openGauss community

Oracle, TimesTen Performance Software, HP

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

Initial release

2012

2004

2019

1998

Current release

Dec2023 (11.49), December 2023

3.0, March 2022

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

Open Source

GPLv2

Open Source

Mozilla Public License 2.0

Open Source

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

C, C++, Java

Server operating systems

server-less

FreeBSD
Linux
OS X
Solaris
Windows

Linux

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

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

SQL

Support of SQL

yes

SQL 2003 with some extensions

ANSI SQL 2011

yes

APIs and other access methods

in-process shared library

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

JDBC
ODBC

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

Supported programming languages

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

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

C
C++
Java

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes, in SQL, C, R

yes

PL/SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding via remote tables

horizontal partitioning (by range, list and hash)

none

Replication methods

Methods for redundantly storing data on multiple nodes

none

Source-replica replication available in experimental status

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users, groups and roles according to SQL-standard

fine grained access rights according to SQL-standard

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

In 2024 the MonetDB Foundation was established for the preservation, maintenance and further development of the ...
31 January 2024, Centrum Wiskunde & Informatica (CWI)

MonetDB Secures Investment From (and Partners With) ServiceNow
9 December 2021, Datanami

PostgreSQL, MonetDB, and Too-Big-for-Memory Data in R - Part I - DataScienceCentral.com
6 April 2018, Data Science Central

How MonetDB Exploits Modern CPU Performance | by Dwi Prasetyo Adi Nugroho
14 January 2020, Towards Data Science

Monet DB The Column-Store Pioneer - open source for you
4 September 2019, Open Source For You

provided by Google News

openGauss Open Source Community Officially Launch
1 July 2020, Huawei

The openGauss powers database industry forward through innovation
6 January 2022, Global Times

Engineering Students from Thammasat Win 2 'Huawei ICT' Awards to Represent Thailand in Asia-Pacific Competition.
12 January 2024, tu.ac.th

Diversified Computing: Open Innovation for Shared Success
30 September 2020, Huawei

Huawei unveils OrangePi Kunpeng Pro development board
10 May 2024, HC Newsroom

provided by Google News

Share this page