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DBMS > Atos Standard Common Repository vs. Kinetica vs. Kyligence Enterprise vs. Spark SQL

System Properties Comparison Atos Standard Common Repository vs. Kinetica vs. Kyligence Enterprise vs. Spark SQL

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonKinetica  Xexclude from comparisonKyligence Enterprise  Xexclude from comparisonSpark SQL  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 networksFully vectorized database across both GPUs and CPUsA distributed analytics engine for big data, built on top of Apache KylinSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument store
Key-value store
Relational DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score0.40
Rank#269  Overall
#124  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.kinetica.comkyligence.io/­kyligence-enterprisespark.apache.org/­sql
Technical documentationdocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAtos Convergence CreatorsKineticaKyligence, Inc.Apache Software Foundation
Initial release2016201220162014
Current release17037.1, August 20213.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen 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, C++JavaScala
Server operating systemsLinuxLinuxLinuxLinux
OS X
Windows
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 indexesyesyesyesno
SQL infoSupport of SQLnoSQL-like DML and DDL statementsANSI SQL for queries (using Apache Calcite)SQL-like DML and DDL statements
APIs and other access methodsLDAPJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
RESTful HTTP API
JDBC
ODBC
Supported programming languagesAll languages with LDAP bindingsC++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functionsno
Triggersyesyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesno
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.yesyes infoGPU vRAM or System RAMnono
User concepts infoAccess controlLDAP bind authenticationAccess rights for users and roles on table levelno

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Atos Standard Common RepositoryKineticaKyligence EnterpriseSpark SQL
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