DBMS > Atos Standard Common Repository vs. Hive vs. IBM Db2 vs. RDF4J vs. SAP HANA

System Properties Comparison Atos Standard Common Repository vs. Hive vs. IBM Db2 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

data warehouse software for querying and managing large distributed datasets, built on Hadoop

Common in IBM host environments, 2 different versions for host and Windows/Linux

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

Relational DBMS

Since Version 10.5 support for JSON/BSON documents compatible with MongoDB

RDF store

Relational DBMS

Secondary database models

Document store
RDF store

in Db2 LUW (Linux, Unix, Windows)
Spatial DBMS

with Db2 Spatial Extender

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

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

Score	61.17
Rank	#18	Overall
	#12	Relational DBMS

Score	128.46
Rank	#8	Overall
	#5	Relational DBMS

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

hive.apache.org

www.ibm.com/products/db2

rdf4j.org

www.sap.com/products/hana.html

Technical documentation

cwiki.apache.org/confluence/display/Hive/Home

www.ibm.com/docs/en/db2

rdf4j.org/documentation

help.sap.com/hana

Developer

Atos Convergence Creators

Apache Software Foundation

initially developed by Facebook

IBM

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

SAP

Initial release

2016

2012

1983

host version

2004

2010

Current release

1703

3.1.3, April 2022

12.1, October 2016

2.0 SPS07 (April 4, 2023), April 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

free version is 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 and C++

Java

Server operating systems

Linux

All OS with a Java VM

AIX
HP-UX
Linux
Solaris
Windows
z/OS

Linux
OS X
Unix
Windows

Appliance or cloud-service

Data scheme

Schema and schema-less with LDAP views

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-like DML and DDL statements

yes

APIs and other access methods

LDAP

JDBC
ODBC
Thrift

ADO.NET
JDBC
JSON style queries

MongoDB compatible
ODBC
XQuery

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

C++
Java
PHP
Python

C
C#
C++
Cobol
Delphi
Fortran
Java
Perl
PHP
Python
Ruby
Visual Basic

Java
PHP
Python

Server-side scripts

Stored procedures

yes

user defined functions and integration of map-reduce

yes

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

only with Windows/Unix/Linux Version

none

yes

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

yes

with separate tools (MQ, InfoSphere)

none

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

query execution via MapReduce

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Eventual 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

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

User concepts

Access control

LDAP bind authentication

Access rights for users, groups and roles

fine grained access rights according to SQL-standard

yes

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