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DBMS > Atos Standard Common Repository vs. gStore vs. Spark SQL vs. Yaacomo

System Properties Comparison Atos Standard Common Repository vs. gStore vs. Spark SQL vs. Yaacomo

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisongStore  Xexclude from comparisonSpark SQL  Xexclude from comparisonYaacomo  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksA native Graph DBMS to store and maintain very large RDF datasets.Spark SQL is a component on top of 'Spark Core' for structured data processingOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelDocument store
Key-value store
Graph DBMS
RDF store
Relational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.14
Rank#342  Overall
#34  Graph DBMS
#16  RDF stores
Score18.04
Rank#33  Overall
#20  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositoryen.gstore.cnspark.apache.org/­sqlyaacomo.com
Technical documentationen.gstore.cn/­#/­enDocsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAtos Convergence CreatorsApache Software FoundationQ2WEB GmbH
Initial release2016201620142009
Current release17031.2, November 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoBSDOpen Source infoApache 2.0commercial
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++Scala
Server operating systemsLinuxLinuxLinux
OS X
Windows
Android
Linux
Windows
Data schemeSchema and schema-less with LDAP viewsschema-free and OWL/RDFS-schema supportyesyes
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 indexesyesnoyes
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsyes
APIs and other access methodsLDAPHTTP API
SPARQL 1.1
JDBC
ODBC
JDBC
ODBC
Supported programming languagesAll languages with LDAP bindingsC++
Java
JavaScript (Node.js)
PHP
Python
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoyesno
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionyes, utilizing Spark Corehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesyesnoneSource-replica replication
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 Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsyesnoACID
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.yesnonoyes
User concepts infoAccess controlLDAP bind authenticationUsers, roles and permissions, Role-Based Access Control (RBAC) supportednofine grained access rights according to SQL-standard

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More resources
Atos Standard Common RepositorygStoreSpark SQLYaacomo
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