DBMS > Atos Standard Common Repository vs. GBase vs. Infobright vs. TimescaleDB vs. Yaacomo

System Properties Comparison Atos Standard Common Repository vs. GBase vs. Infobright vs. TimescaleDB 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

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

A time series DBMS optimized for fast ingest and complex queries, based on PostgreSQL

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

Primary database model

Document store
Key-value store

Relational DBMS

Time Series DBMS

Relational DBMS

Secondary database models

Relational DBMS

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

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	4.64
Rank	#71	Overall
	#4	Time Series DBMS

Website

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

www.gbase.cn

ignitetech.com/softwarelibrary/infobrightdb

www.timescale.com

yaacomo.com

Technical documentation

docs.timescale.com

Developer

Atos Convergence Creators

General Data Technology Co., Ltd.

Ignite Technologies Inc.; formerly InfoBright Inc.

Timescale

Q2WEB GmbH

Initial release

2016

2004

2005

2017

2009

Current release

1703

GBase 8a, GBase 8s, GBase 8c

2.13.0, November 2023

License

Commercial or Open Source

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

Apache 2.0

commercial

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

C, Java, Python

Server operating systems

Linux

Linux
Windows

Linux
OS X
Windows

Android
Linux
Windows

Data scheme

Schema and schema-less with LDAP views

yes

Typing

predefined data types such as float or date

optional

yes

numerics, strings, booleans, arrays, JSON blobs, geospatial dimensions, currencies, binary data, other complex data types

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

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

Standard with numerous extensions

yes

full PostgreSQL SQL syntax

yes

APIs and other access methods

LDAP

ADO.NET
C API
JDBC
ODBC

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

JDBC
ODBC

Supported programming languages

All languages with LDAP bindings

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C
C++
Delphi
Java

JDBC
JavaScript
Perl
PHP
Python
R
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

user defined functions

user defined functions, PL/pgSQL, PL/Tcl, PL/Perl, PL/Python, PL/Java, PL/PHP, PL/R, PL/Ruby, PL/Scheme, PL/Unix shell

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

horizontal partitioning (by range, list and hash) and vertical partitioning

none

yes, across time and space (hash partitioning) attributes

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

Source-replica replication with hot standby and reads on replicas

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

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

yes

fine grained access rights according to SQL-standard

exploiting MySQL or PostgreSQL frontend capabilities

fine grained access rights according to SQL-standard

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