DBMS > Atos Standard Common Repository vs. EDB Postgres vs. GridDB vs. SQream DB vs. Stardog

System Properties Comparison Atos Standard Common Repository vs. EDB Postgres vs. GridDB vs. SQream DB vs. Stardog

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

The EDB Postgres Platform is an enterprise-class data management platform based on the open source database PostgreSQL with flexible deployment options and Oracle compatibility features, complemented by tool kits for management, integration, and migration.

Scalable in-memory time series database optimized for IoT and Big Data

a GPU-based, columnar RDBMS for big data analytics workloads

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Document store
Key-value store

Secondary database models

Document store
Spatial DBMS

Key-value store
Relational DBMS

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

Score	1.86
Rank	#131	Overall
	#61	Relational DBMS

Score	1.91
Rank	#123	Overall
	#10	Time Series DBMS

Score	0.62
Rank	#234	Overall
	#109	Relational DBMS

Score	1.93
Rank	#121	Overall
	#10	Graph DBMS
	#6	RDF stores

Website

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

Technical documentation

www.enterprisedb.com/docs

docs.griddb.net

docs.sqream.com

docs.stardog.com

Developer

Atos Convergence Creators

EnterpriseDB

Toshiba Corporation

SQream Technologies

Stardog-Union

Initial release

2016

2005

2013

2017

2010

Current release

1703

14, December 2021

5.1, August 2022

2022.1.6, December 2022

7.3.0, May 2020

License

Commercial or Open Source

commercial

BSD for PostgreSQL-components

Open Source

AGPL version 3 and Apache License, version 2.0 , commercial license (standard and advanced editions) also available

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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++

C++, CUDA, Haskell, Java, Scala

Java

Server operating systems

Linux

Linux
Windows

Linux

Linux
macOS
Windows

Data scheme

Schema and schema-less with LDAP views

yes

schema-free and OWL/RDFS-schema support

Typing

predefined data types such as float or date

optional

yes

numerical, string, blob, geometry, boolean, timestamp

yes, ANSI Standard SQL 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

specific XML-type available, but no XML query functionality.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

standard with numerous extensions

SQL92, SQL-like TQL (Toshiba Query Language)

yes

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

LDAP

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

JDBC
ODBC
Proprietary protocol
RESTful HTTP/JSON API

.Net
JDBC
ODBC

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

All languages with LDAP bindings

.Net
C
C++
Delphi
Java
Perl
PHP
Python
Tcl

C
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

user defined functions in Python

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

horizontal partitioning

by hash, list or range

Sharding

horizontal and vertical partitioning

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication

Source-replica replication

none

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

Connector for using GridDB as an input source and output destination for Hadoop MapReduce jobs

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Immediate consistency within container, eventual consistency across containers

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

Atomic execution of specific operations

ACID

ACID at container level

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

fine grained access rights according to SQL-standard

Access rights for users can be defined per database

Access rights for users and roles

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