DBMS > Atos Standard Common Repository vs. MonetDB vs. Newts vs. Percona Server for MongoDB vs. Trafodion

System Properties Comparison Atos Standard Common Repository vs. MonetDB vs. Newts vs. Percona Server for MongoDB vs. Trafodion

Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

Description

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

A relational database management system that stores data in columns

Time Series DBMS based on Cassandra

A drop-in replacement for MongoDB Community Edition with enterprise-grade features.

Transactional SQL-on-Hadoop DBMS

Primary database model

Document store
Key-value store

Secondary database models

Document store
Spatial DBMS

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

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	0.52
Rank	#254	Overall
	#39	Document stores

Website

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.monetdb.org

opennms.github.io/newts

www.percona.com/mongodb/software/percona-server-for-mongodb

trafodion.apache.org

Technical documentation

www.monetdb.org/Documentation

github.com/OpenNMS/newts/wiki

docs.percona.com/percona-distribution-for-mongodb

trafodion.apache.org/documentation.html

Developer

Atos Convergence Creators

MonetDB BV

OpenNMS Group

Percona

Apache Software Foundation, originally developed by HP

Initial release

2016

2004

2014

2015

2014

Current release

1703

Dec2023 (11.49), December 2023

3.4.10-2.10, November 2017

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

Mozilla Public License 2.0

Open Source

Apache 2.0

Open Source

GPL Version 2

Open Source

Apache 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++

C++, Java

Server operating systems

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Linux

Data scheme

Schema and schema-less with LDAP views

yes

schema-free

yes

Typing

predefined data types such as float or date

optional

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

SQL

Support of SQL

yes

SQL 2003 with some extensions

yes

APIs and other access methods

LDAP

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

HTTP REST
Java API

proprietary protocol using JSON

ADO.NET
JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

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

Java

Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

yes, in SQL, C, R

JavaScript

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding via remote tables

Sharding

based on Cassandra

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication available in experimental status

selectable replication factor

based on Cassandra

Source-replica replication

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

via user defined functions and HBase

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

Atomic execution of specific operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

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

yes

via In-Memory Engine

User concepts

Access control

LDAP bind authentication

fine grained access rights according to SQL-standard

Access rights for users and roles

fine grained access rights according to SQL-standard

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