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

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

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonCoveo  Xexclude from comparisonSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  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 networksAI-powered hosted search, recommendation and personalization platform providing tools for both low-code and full-code developmentSpark SQL is a component on top of 'Spark Core' for structured data processingA high performance, scalable Wide Column DBMS
Primary database modelDocument store
Key-value store
Search engineRelational DBMSWide column store
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.11
Rank#118  Overall
#11  Search engines
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-repositorywww.coveo.comspark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
Technical documentationdocs.coveo.comspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperAtos Convergence CreatorsCoveoApache Software FoundationAlex Kashirin
Initial release2016201220142020
Current release17033.5.0 ( 2.13), September 20230.5, April 2021
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0Open Source infoGPL V3
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScalaC++
Server operating systemsLinuxhostedLinux
OS X
Windows
Linux
Data schemeSchema and schema-less with LDAP viewshybrid - fields need to be configured prior to indexing, but relationships can be exploited at query time without pre-configurationyesschema-free
Typing infopredefined data types such as float or dateoptionalyesyes
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 indexesyesyesno
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsSQL-like query language
APIs and other access methodsLDAPRESTful HTTP APIJDBC
ODBC
Proprietary protocol
Thrift
Supported programming languagesAll languages with LDAP bindingsC#
Java
JavaScript
Python
Java
Python
R
Scala
C++
Server-side scripts infoStored proceduresnononono
Triggersyesyesnono
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionyesyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesyesnone
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 integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsyesno
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 authenticationgranular access controls, API key management, content filtersno

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More resources
Atos Standard Common RepositoryCoveoSpark SQLSWC-DB infoSuper Wide Column Database
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