DBMS > Atos Standard Common Repository vs. gStore vs. SAP HANA vs. SWC-DB vs. Yaacomo

System Properties Comparison Atos Standard Common Repository vs. gStore vs. SAP HANA vs. SWC-DB vs. Yaacomo

Editorial information provided by DB-Engines

Name

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

Yaacomo seems to be discontinued and is removed from the DB-Engines ranking

Description

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

A native Graph DBMS to store and maintain very large RDF datasets.

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

A high performance, scalable Wide Column DBMS

OpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing

Primary database model

Document store
Key-value store

Secondary database models

Document store
Graph DBMS

with SAP Hana, Enterprise Edition
Spatial DBMS

Time Series DBMS

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

Score	0.14
Rank	#342	Overall
	#34	Graph DBMS
	#16	RDF stores

Score	44.27
Rank	#23	Overall
	#16	Relational DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

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

en.gstore.cn

www.sap.com/products/hana.html

github.com/kashirin-alex/swc-db
www.swcdb.org

yaacomo.com

Technical documentation

en.gstore.cn/#/enDocs

help.sap.com/hana

Developer

Atos Convergence Creators

SAP

Alex Kashirin

Q2WEB GmbH

Initial release

2016

2010

2020

2009

Current release

1703

1.2, November 2023

2.0 SPS07 (April 4, 2023), April 2023

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

BSD

commercial

Open Source

GPL V3

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++

Server operating systems

Linux

Appliance or cloud-service

Linux

Android
Linux
Windows

Data scheme

Schema and schema-less with LDAP views

schema-free and OWL/RDFS-schema support

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-like query language

yes

APIs and other access methods

LDAP

HTTP API
SPARQL 1.1

JDBC
ODBC

Proprietary protocol
Thrift

JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

C++
Java
JavaScript (Node.js)
PHP
Python

C++

Server-side scripts

Stored procedures

yes

SQLScript, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

yes

Sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

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

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

yes

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

User concepts

Access control

LDAP bind authentication

Users, roles and permissions, Role-Based Access Control (RBAC) supported

yes

fine grained access rights according to SQL-standard

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