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

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

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparisonYanza  Xexclude from comparison
This system has been discontinued and will be removed from the DB-Engines ranking.Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionHighly scalable database system, designed for managing session and subscriber data in modern mobile communication networksSpark SQL is a component on top of 'Spark Core' for structured data processingA high performance, scalable Wide Column DBMSTime Series DBMS for IoT Applications
Primary database modelDocument store
Key-value store
Relational DBMSWide column storeTime Series DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
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-repositoryspark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
yanza.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAtos Convergence CreatorsApache Software FoundationAlex KashirinYanza
Initial release2016201420202015
Current release17033.5.0 ( 2.13), September 20230.5, April 2021
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open Source infoGPL V3commercial infofree version available
Cloud-based only infoOnly available as a cloud servicenononono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScalaC++
Server operating systemsLinuxLinux
OS X
Windows
LinuxWindows
Data schemeSchema and schema-less with LDAP viewsyesschema-freeschema-free
Typing infopredefined data types such as float or dateoptionalyesno
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 SQLnoSQL-like DML and DDL statementsSQL-like query languageno
APIs and other access methodsLDAPJDBC
ODBC
Proprietary protocol
Thrift
HTTP API
Supported programming languagesAll languages with LDAP bindingsJava
Python
R
Scala
C++any language that supports HTTP calls
Server-side scripts infoStored proceduresnononono
Triggersyesnonoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionyes, utilizing Spark CoreShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesyesnonenone
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.yesnono
User concepts infoAccess controlLDAP bind authenticationnono

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More resources
Atos Standard Common RepositorySpark SQLSWC-DB infoSuper Wide Column DatabaseYanza
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