DBMS > Atos Standard Common Repository vs. EJDB vs. Newts vs. Oracle NoSQL vs. RDF4J

System Properties Comparison Atos Standard Common Repository vs. EJDB vs. Newts vs. Oracle NoSQL vs. RDF4J

Editorial information provided by DB-Engines

Name

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

Description

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

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

Time Series DBMS based on Cassandra

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

RDF4J is a Java framework for processing RDF data, supporting both memory-based and a disk-based storage.

Primary database model

Document store
Key-value store

Document store

Time Series DBMS

Document store
Key-value store
Relational DBMS

RDF store

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

Score	0.27
Rank	#297	Overall
	#44	Document stores

Score	0.00
Rank	#383	Overall
	#41	Time Series DBMS

Score	2.95
Rank	#100	Overall
	#17	Document stores
	#17	Key-value stores
	#50	Relational DBMS

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Website

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

github.com/Softmotions/ejdb

opennms.github.io/newts

www.oracle.com/database/nosql/technologies/nosql

rdf4j.org

Technical documentation

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

github.com/OpenNMS/newts/wiki

docs.oracle.com/en/database/other-databases/nosql-database/index.html

rdf4j.org/documentation

Developer

Atos Convergence Creators

Softmotions

OpenNMS Group

Oracle

Since 2016 officially forked into an Eclipse project, former developer was Aduna Software.

Initial release

2016

2012

2014

2011

2004

Current release

1703

23.3, December 2023

License

Commercial or Open Source

commercial

Open Source

GPLv2

Open Source

Apache 2.0

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

Eclipse Distribution License (EDL), v1.0.

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

Server operating systems

Linux

server-less

Linux
OS X
Windows

Linux
Solaris SPARC/x86

Linux
OS X
Unix
Windows

Data scheme

Schema and schema-less with LDAP views

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

RDF Schemas

Typing

predefined data types such as float or date

optional

yes

string, integer, double, bool, date, object_id

yes

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

SQL-like DML and DDL statements

APIs and other access methods

LDAP

in-process shared library

HTTP REST
Java API

RESTful HTTP API

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

Supported programming languages

All languages with LDAP bindings

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

Java

C
C#
Go
Java
JavaScript (Node.js)
Python

Java
PHP
Python

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Sharding

based on Cassandra

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

based on Cassandra

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

none

MapReduce

Offers an API for user-defined Map/Reduce methods

with Hadoop integration

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

depending on configuration

Foreign keys

Referential integrity

typically not needed, however similar functionality with collection joins possible

Transaction concepts

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

Atomic execution of specific operations

configurable

ACID within a storage node (=shard)

ACID

Isolation support depends on the API used

Concurrency

Support for concurrent manipulation of data

yes

Read/Write Locking

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

In-memory capabilities

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

yes

off heap cache

User concepts

Access control

LDAP bind authentication

Access rights for users and roles

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