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DBMS > Atos Standard Common Repository vs. Kinetica vs. Spark SQL vs. Splice Machine vs. SQream DB

System Properties Comparison Atos Standard Common Repository vs. Kinetica vs. Spark SQL vs. Splice Machine vs. SQream DB

Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonKinetica  Xexclude from comparisonSpark SQL  Xexclude from comparisonSplice Machine  Xexclude from comparisonSQream DB  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 CPUsSpark SQL is a component on top of 'Spark Core' for structured data processingOpen-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Sparka GPU-based, columnar RDBMS for big data analytics workloads
Primary database modelDocument store
Key-value store
Relational DBMSRelational 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
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.54
Rank#250  Overall
#114  Relational DBMS
Score0.70
Rank#227  Overall
#104  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.kinetica.comspark.apache.org/­sqlsplicemachine.comsqream.com
Technical documentationdocs.kinetica.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsplicemachine.com/­how-it-worksdocs.sqream.com
DeveloperAtos Convergence CreatorsKineticaApache Software FoundationSplice MachineSQream Technologies
Initial release20162012201420142017
Current release17037.1, August 20213.5.0 ( 2.13), September 20233.1, March 20212022.1.6, December 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoAGPL 3.0, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++ScalaJavaC++, CUDA, Haskell, Java, Scala
Server operating systemsLinuxLinuxLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Linux
Data schemeSchema and schema-less with LDAP viewsyesyesyesyes
Typing infopredefined data types such as float or dateoptionalyesyesyesyes, ANSI Standard SQL Types
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.yesnono
Secondary indexesyesyesnoyesno
SQL infoSupport of SQLnoSQL-like DML and DDL statementsSQL-like DML and DDL statementsyesyes
APIs and other access methodsLDAPJDBC
ODBC
RESTful HTTP API
JDBC
ODBC
JDBC
Native Spark Datasource
ODBC
.Net
JDBC
ODBC
Supported programming languagesAll languages with LDAP bindingsC++
Java
JavaScript (Node.js)
Python
Java
Python
R
Scala
C#
C++
Java
JavaScript (Node.js)
Python
R
Scala
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnouser defined functionsnoyes infoJavauser defined functions in Python
Triggersyesyes infotriggers when inserted values for one or more columns fall within a specified rangenoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingyes, utilizing Spark CoreShared Nothhing Auto-Sharding, Columnar Partitioninghorizontal and vertical partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationnoneMulti-source replication
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoYes, via Full Spark Integrationno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnonoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlLDAP bind authenticationAccess rights for users and roles on table levelnoAccess rights for users, groups and roles according to SQL-standard

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More resources
Atos Standard Common RepositoryKineticaSpark SQLSplice MachineSQream DB
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