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DBMS > Atos Standard Common Repository vs. PostGIS vs. Spark SQL vs. SWC-DB

System Properties Comparison Atos Standard Common Repository vs. PostGIS vs. Spark SQL vs. SWC-DB

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonPostGIS  Xexclude from comparisonSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksSpatial extension of PostgreSQLSpark SQL is a component on top of 'Spark Core' for structured data processingA high performance, scalable Wide Column DBMS
Primary database modelDocument store
Key-value store
Spatial DBMSRelational DBMSWide column store
Secondary database modelsRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score22.69
Rank#29  Overall
#1  Spatial DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.01
Rank#376  Overall
#13  Wide column stores
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorypostgis.netspark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationpostgis.net/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAtos Convergence CreatorsApache Software FoundationAlex Kashirin
Initial release2016200520142020
Current release17033.4.2, February 20243.5.0 ( 2.13), September 20230.5, April 2021
License infoCommercial or Open SourcecommercialOpen Source infoGPL v2.0Open Source infoApache 2.0Open Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCScalaC++
Server operating systemsLinuxLinux
OS X
Windows
Linux
Data schemeSchema and schema-less with LDAP viewsyesyesschema-free
Typing infopredefined data types such as float or dateoptionalyesyes
XML support infoSome form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.yesyesnono
Secondary indexesyesyesno
SQL infoSupport of SQLnoyesSQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsLDAPJDBC
ODBC
Proprietary protocol
Thrift
Supported programming languagesAll languages with LDAP bindingsJava
Python
R
Scala
C++
Server-side scripts infoStored proceduresnouser defined functionsnono
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionyes infobased on PostgreSQLyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyes infobased on PostgreSQLnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnonono
User concepts infoAccess controlLDAP bind authenticationyes infobased on PostgreSQLno

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More resources
Atos Standard Common RepositoryPostGISSpark SQLSWC-DB infoSuper Wide Column Database
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