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DBMS > Atos Standard Common Repository vs. SpaceTime vs. Spark SQL vs. Trafodion

System Properties Comparison Atos Standard Common Repository vs. SpaceTime vs. Spark SQL vs. Trafodion

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonSpaceTime  Xexclude from comparisonSpark SQL  Xexclude from comparisonTrafodion  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.Apache Trafodion has been retired in 2021. Therefore it is excluded 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 processingTransactional SQL-on-Hadoop DBMS
Primary database modelDocument store
Key-value store
Spatial DBMSRelational DBMSRelational DBMS
Secondary database modelsRelational 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
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.mireo.com/­spacetimespark.apache.org/­sqltrafodion.apache.org
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.html
DeveloperAtos Convergence CreatorsMireoApache Software FoundationApache Software Foundation, originally developed by HP
Initial release2016202020142014
Current release17033.5.0 ( 2.13), September 20232.3.0, February 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoApache 2.0
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++, Java
Server operating systemsLinuxLinuxLinux
OS X
Windows
Linux
Data schemeSchema and schema-less with LDAP viewsyesyesyes
Typing infopredefined data types such as float or dateoptionalyesyesyes
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 indexesyesnonoyes
SQL infoSupport of SQLnoA subset of ANSI SQL is implementedSQL-like DML and DDL statementsyes
APIs and other access methodsLDAPRESTful HTTP APIJDBC
ODBC
ADO.NET
JDBC
ODBC
Supported programming languagesAll languages with LDAP bindingsC#
C++
Python
Java
Python
R
Scala
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnononoJava Stored Procedures
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)noneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnonoACID
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 authenticationyesnofine grained access rights according to SQL-standard

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More resources
Atos Standard Common RepositorySpaceTimeSpark SQLTrafodion
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