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

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

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonSpaceTime  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 networksSpaceTime is a spatio-temporal DBMS with a focus on performance.Spark 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
Score0.03
Rank#392  Overall
#8  Spatial DBMS
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.08
Rank#364  Overall
#13  Wide column stores
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.mireo.com/­spacetimespark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAtos Convergence CreatorsMireoApache Software FoundationAlex Kashirin
Initial release2016202020142020
Current release17033.5.0 ( 2.13), September 20230.5, April 2021
License infoCommercial or Open SourcecommercialcommercialOpen 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 languageJavaC++ScalaC++
Server operating systemsLinuxLinuxLinux
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.yesnonono
Secondary indexesyesnono
SQL infoSupport of SQLnoA subset of ANSI SQL is implementedSQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsLDAPRESTful HTTP APIJDBC
ODBC
Proprietary protocol
Thrift
Supported programming languagesAll languages with LDAP bindingsC#
C++
Python
Java
Python
R
Scala
C++
Server-side scripts infoStored proceduresnononono
Triggersyesnonono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionFixed-grid hypercubesyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesReal-time block device replication (DRBD)none
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 integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnono
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 authenticationyesno

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