DBMS > Atos Standard Common Repository vs. Greenplum vs. Postgres-XL vs. RisingWave

System Properties Comparison Atos Standard Common Repository vs. Greenplum vs. Postgres-XL vs. RisingWave

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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

Analytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database

A logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

A distributed RDBMS for stream processing, wire-compatible with PostgreSQL

Primary database model

Document store
Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	8.37
Rank	#48	Overall
	#30	Relational DBMS

Score	0.49
Rank	#256	Overall
	#117	Relational DBMS

Score	0.58
Rank	#242	Overall
	#111	Relational DBMS

Website

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

greenplum.org

www.postgres-xl.org

www.risingwave.com/database

Technical documentation

docs.greenplum.org

www.postgres-xl.org/documentation

docs.risingwave.com/docs/current/intro

Developer

Atos Convergence Creators

Pivotal Software Inc.

RisingWave Labs

Initial release

2016

2005

2014

since 2012, originally named StormDB

2022

Current release

1703

7.0.0, September 2023

10 R1, October 2018

1.2, September 2023

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

Open Source

Mozilla public license

Open Source

Apache Version 2.0

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

Rust

Server operating systems

Linux

Linux
macOS

Docker
Linux
macOS

Data scheme

Schema and schema-less with LDAP views

yes

Typing

predefined data types such as float or date

optional

yes

Standard SQL-types and JSON

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

since Version 4.2

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

yes

APIs and other access methods

LDAP

JDBC
ODBC

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

JDBC
PostgreSQL wire protocol

Supported programming languages

All languages with LDAP bindings

C
Java
Perl
Python
R

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Go
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

UDFs in Python or Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

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

yes

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

MVCC

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

fine grained access rights according to SQL-standard

Users and Roles

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