DBMS > Atos Standard Common Repository vs. EventStoreDB vs. RDF4J vs. XTDB

System Properties Comparison Atos Standard Common Repository vs. EventStoreDB vs. RDF4J vs. XTDB

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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

Industrial-strength, open-source database solution built from the ground up for event sourcing.

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Document store
Key-value store

Event Store

RDF store

Document store

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

Score	1.14
Rank	#181	Overall
	#1	Event Stores

Score	0.71
Rank	#231	Overall
	#9	RDF stores

Score	0.09
Rank	#351	Overall
	#47	Document stores

Website

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

www.eventstore.com

rdf4j.org

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

developers.eventstore.com

rdf4j.org/documentation

www.xtdb.com/docs

Developer

Atos Convergence Creators

Event Store Limited

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

Juxt Ltd.

Initial release

2016

2012

2004

2019

Current release

1703

21.2, February 2021

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

Eclipse Distribution License (EDL), v1.0.

Open Source

MIT License

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

Clojure

Server operating systems

Linux

Linux
Windows

Linux
OS X
Unix
Windows

All OS with a Java 8 (and higher) VM
Linux

Data scheme

Schema and schema-less with LDAP views

yes

RDF Schemas

schema-free

Typing

predefined data types such as float or date

optional

yes

yes, extensible-data-notation format

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

limited SQL, making use of Apache Calcite

APIs and other access methods

LDAP

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

HTTP REST
JDBC

Supported programming languages

All languages with LDAP bindings

Java
PHP
Python

Clojure
Java

Server-side scripts

Stored procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

Transaction concepts

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

Atomic execution of specific operations

ACID

Isolation support depends on the API used

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

in-memory storage is supported as well

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

yes

User concepts

Access control

LDAP bind authentication

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