DBMS > Atos Standard Common Repository vs. Postgres-XL vs. Sadas Engine vs. Teradata Aster

System Properties Comparison Atos Standard Common Repository vs. Postgres-XL vs. Sadas Engine vs. Teradata Aster

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Editorial information provided by DB-Engines
Name	Atos Standard Common Repository  Xexclude from comparison	Postgres-XL  Xexclude from comparison	Sadas Engine  Xexclude from comparison	Teradata Aster  Xexclude from comparison
	This system has been discontinued and will be removed from the DB-Engines ranking.			Teradata Aster has been integrated into other Teradata systems and therefore 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	Based on PostgreSQL enhanced with MPP and write-scale-out cluster features	SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments	Platform for big data analytics on multistructured data sources and types
Primary database model	Document store Key-value store	Relational DBMS	Relational DBMS	Relational DBMS
Secondary database models		Document store Spatial DBMS
DB-Engines Ranking measures the popularity of database management systems Trend Chart		Score 0.53 Rank #254   Overall #117   Relational DBMS	Score 0.07 Rank #373   Overall #157   Relational DBMS
Website	atos.net/en/convergence-creators/portfolio/standard-common-repository	www.postgres-xl.org	www.sadasengine.com
Technical documentation		www.postgres-xl.org/­documentation	www.sadasengine.com/­en/­sadas-engine-download-free-trial-and-documentation/­#documentation
Developer	Atos Convergence Creators		SADAS s.r.l.	Teradata
Initial release	2016	2014 since 2012, originally named StormDB	2006	2005
Current release	1703	10 R1, October 2018	8.0
License Commercial or Open Source	commercial	Open Source Mozilla public license	commercial free trial version available	commercial
Cloud-based only Only available as a cloud service	no	no	no	no
DBaaS offerings (sponsored links) Database as a Service Providers of DBaaS offerings, please contact us to be listed.
Implementation language	Java	C	C++
Server operating systems	Linux	Linux macOS	AIX Linux Windows	Linux
Data scheme	Schema and schema-less with LDAP views	yes	yes	Flexible Schema (defined schema, partial schema, schema free) defined schema within the relational store; partial schema or schema free in the Aster File Store
Typing predefined data types such as float or date	optional	yes	yes	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	yes XML type, but no XML query functionality	no	yes in Aster File Store
Secondary indexes	yes	yes	yes	yes
SQL Support of SQL	no	yes distributed, parallel query execution	yes	yes
APIs and other access methods	LDAP	ADO.NET JDBC native C library ODBC streaming API for large objects	JDBC ODBC Proprietary protocol	ADO.NET JDBC ODBC OLE DB
Supported programming languages	All languages with LDAP bindings	.Net C C++ Delphi Erlang Java JavaScript (Node.js) Perl PHP Python Tcl	.Net C C# C++ Groovy Java PHP Python	C C# C++ Java Python R
Server-side scripts Stored procedures	no	user defined functions	no	R packages
Triggers	yes	yes	no	no
Partitioning methods Methods for storing different data on different nodes	Sharding cell division	horizontal partitioning	horizontal partitioning	Sharding
Replication methods Methods for redundantly storing data on multiple nodes	yes		none	yes Dimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.
MapReduce Offers an API for user-defined Map/Reduce methods		no	no	yes SQL Map-Reduce Framework
Consistency concepts Methods to ensure consistency in a distributed system	Immediate Consistency or Eventual Consistency depending on configuration	Immediate Consistency	Immediate Consistency	Immediate Consistency or Eventual Consistency depending on configuration
Foreign keys Referential integrity	no	yes	yes	no
Transaction concepts Support to ensure data integrity after non-atomic manipulations of data	Atomic execution of specific operations	ACID MVCC		ACID
Concurrency Support for concurrent manipulation of data	yes	yes	yes	yes
Durability Support for making data persistent	yes	yes	yes	yes
In-memory capabilities Is there an option to define some or all structures to be held in-memory only.	yes	no	yes managed by 'Learn by Usage'	no
User concepts Access control	LDAP bind authentication	fine grained access rights according to SQL-standard	Access rights for users, groups and roles according to SQL-standard	fine grained access rights according to SQL-standard
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More resources
	Atos Standard Common Repository	Postgres-XL	Sadas Engine	Teradata Aster
Recent citations in the news				Teradata Enhances Big Data Analytics Platform 31 May 2024, Data Center Knowledge Northwestern Analytics Partners with Teradata Aster to Host Hackathon 23 May 2014, Northwestern Engineering Teradata Provides the Simplest Way to Bring the Science of Data to the Art of Business 22 September 2011, PR Newswire Teradata's Aster shows how the flowers of fraud bloom 23 April 2015, The Register Teradata unveils improved QueryGrid connectors 21 April 2015, CIO provided by Google News

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