DBMS > Amazon Redshift vs. Atos Standard Common Repository vs. GridGain vs. Oracle Rdb

System Properties Comparison Amazon Redshift vs. Atos Standard Common Repository vs. GridGain vs. Oracle Rdb

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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

Large scale data warehouse service for use with business intelligence tools

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

GridGain is an in-memory computing platform, built on Apache Ignite

Primary database model

Relational DBMS

Document store
Key-value store

Key-value store
Relational DBMS

Relational DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	1.55
Rank	#150	Overall
	#26	Key-value stores
	#70	Relational DBMS

Score	1.14
Rank	#178	Overall
	#80	Relational DBMS

Website

aws.amazon.com/redshift

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

www.gridgain.com

www.oracle.com/database/technologies/related/rdb.html

Technical documentation

docs.aws.amazon.com/redshift

www.gridgain.com/docs/index.html

www.oracle.com/database/technologies/related/rdb-doc.html

Developer

Amazon (based on PostgreSQL)

Atos Convergence Creators

GridGain Systems, Inc.

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2012

2016

2007

1984

Current release

1703

GridGain 8.5.1

7.4.1.1, 2021

License

Commercial or Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Java

Java, C++, .Net

Server operating systems

hosted

Linux

Linux
OS X
Solaris
Windows

HP Open VMS

Data scheme

yes

Schema and schema-less with LDAP views

yes

Flexible Schema (defined schema, partial schema, schema free)

Typing

predefined data types such as float or date

yes

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

ANSI-99 for query and DML statements, subset of DDL

yes

APIs and other access methods

JDBC
ODBC

LDAP

HDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data

Supported programming languages

All languages supporting JDBC/ODBC

All languages with LDAP bindings

C#
C++
Java
PHP
Python
Ruby
Scala

Server-side scripts

Stored procedures

user defined functions

in Python

yes (compute grid and cache interceptors can be used instead)

Triggers

yes

yes (cache interceptors and events)

Partitioning methods

Methods for storing different data on different nodes

Sharding

cell division

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes (replicated cache)

MapReduce

Offers an API for user-defined Map/Reduce methods

yes (compute grid and hadoop accelerator)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Immediate Consistency

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

Atomic execution of specific operations

ACID

yes, on a single node

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

fine grained access rights according to SQL-standard

LDAP bind authentication

Security Hooks for custom implementations

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