DBMS > Atos Standard Common Repository vs. Couchbase vs. EventStoreDB vs. RDF4J vs. SAP HANA

System Properties Comparison Atos Standard Common Repository vs. Couchbase vs. EventStoreDB vs. RDF4J vs. SAP HANA

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

A distributed document store with integrated cache, a powerful search engine, in-built operational and analytical capabilities, and an embedded mobile database

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.

In-memory, column based data store. Available as appliance or cloud service

Primary database model

Document store
Key-value store

Secondary database models

Key-value store

originating from the former Membase product and supporting the Memcached protocol
Spatial DBMS

using the Geocouch extension
Search engine
Time Series DBMS
Vector DBMS

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	17.30
Rank	#36	Overall
	#5	Document stores

Score	1.10
Rank	#179	Overall
	#1	Event Stores

Score	0.69
Rank	#230	Overall
	#9	RDF stores

Score	44.69
Rank	#22	Overall
	#16	Relational DBMS

Website

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

www.couchbase.com

www.eventstore.com

rdf4j.org

www.sap.com/products/hana.html

Technical documentation

docs.couchbase.com

developers.eventstore.com

rdf4j.org/documentation

help.sap.com/hana

Developer

Atos Convergence Creators

Couchbase, Inc.

Event Store Limited

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

SAP

Initial release

2016

2011

2012

2004

2010

Current release

1703

Server: 7.2, June 2023; Mobile: 3.1, March 2022; Couchbase Capella (DBaaS), June 2023

21.2, February 2021

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Business Source License (BSL 1.1); Commercial licenses also available

Open Source

Eclipse Distribution License (EDL), v1.0.

commercial

Cloud-based only

Only available as a cloud service

also available as a cloud based service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

C, C++, Go and Erlang

Java

Server operating systems

Linux

Linux
OS X
Windows

Linux
Windows

Linux
OS X
Unix
Windows

Appliance or cloud-service

Data scheme

Schema and schema-less with LDAP views

schema-free

yes

RDF Schemas

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

SQL++, extends ANSI SQL to JSON for operational, transactional, and analytic use cases

yes

APIs and other access methods

LDAP

CLI Client
HTTP REST
Kafka Connector
Native language bindings for CRUD, Query, Search and Analytics APIs
Spark Connector
Spring Data

Java API
RIO

RDF Input/Output
Sail API
SeRQL

Sesame RDF Query Language
Sesame REST HTTP Protocol
SPARQL

JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

.Net
C
Go
Java
JavaScript

Node.js
Kotlin
PHP
Python
Ruby
Scala

Java
PHP
Python

Server-side scripts

Stored procedures

Functions and timers in JavaScript and UDFs in Java, Python, SQL++

yes

SQLScript, R

Triggers

yes

via the TAP protocol

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Automatic Sharding

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

including cross data center replication
Source-replica replication

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

selectable on a per-operation basis

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

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

In-memory capabilities

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

yes

Ephemeral buckets

yes

User concepts

Access control

LDAP bind authentication

User and Administrator separation with password-based and LDAP integrated Authentication. Role-base access control.

yes

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