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DBMS > Atos Standard Common Repository vs. Kinetica vs. Microsoft Azure AI Search

System Properties Comparison Atos Standard Common Repository vs. Kinetica vs. Microsoft Azure AI Search

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonKinetica  Xexclude from comparisonMicrosoft Azure AI Search  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 CPUsSearch-as-a-service for web and mobile app development
Primary database modelDocument store
Key-value store
Relational DBMSSearch engine
Secondary database modelsSpatial DBMS
Time Series DBMS
Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorywww.kinetica.comazure.microsoft.com/­en-us/­services/­search
Technical documentationdocs.kinetica.comlearn.microsoft.com/­en-us/­azure/­search
DeveloperAtos Convergence CreatorsKineticaMicrosoft
Initial release201620122015
Current release17037.1, August 2021V1
License infoCommercial or Open Sourcecommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud servicenonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaC, C++
Server operating systemsLinuxLinuxhosted
Data schemeSchema and schema-less with LDAP viewsyesyes
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.yesnono
Secondary indexesyesyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsno
APIs and other access methodsLDAPJDBC
ODBC
RESTful HTTP API
RESTful HTTP API
Supported programming languagesAll languages with LDAP bindingsC++
Java
JavaScript (Node.js)
Python
C#
Java
JavaScript
Python
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 divisionShardingSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesyesSource-replica replicationyes infoImplicit feature of the cloud service
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 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 datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoGPU vRAM or System RAMno
User concepts infoAccess controlLDAP bind authenticationAccess rights for users and roles on table levelyes infousing Azure authentication

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More resources
Atos Standard Common RepositoryKineticaMicrosoft Azure AI Search
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