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DBMS > Atos Standard Common Repository vs. Milvus vs. Spark SQL vs. Transbase

System Properties Comparison Atos Standard Common Repository vs. Milvus vs. Spark SQL vs. Transbase

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Editorial information provided by DB-Engines
NameAtos Standard Common Repository  Xexclude from comparisonMilvus  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  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 networksA DBMS designed for efficient storage of vector data and vector similarity searchesSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelDocument store
Key-value store
Multivalue DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.28
Rank#271  Overall
#11  Multivalue DBMS
Score22.94
Rank#34  Overall
#20  Relational DBMS
Score0.22
Rank#285  Overall
#132  Relational DBMS
Websiteatos.net/en/convergence-creators/portfolio/standard-common-repositorymilvus.iospark.apache.org/­sqlwww.transaction.de/­en/­solutions/­transbase-resource-optimized-high-performance-database
Technical documentationmilvus.io/­docs/­overview.mdspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­transbase-inside
DeveloperAtos Convergence CreatorsApache Software FoundationTransaction Software GmbH
Initial release2016201920141987
Current release17031.0, March 20213.1.1, March 2021Transbase 8.4, September 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2.0Open Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaC++ScalaC and C++
Server operating systemsLinuxLinuxLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Data schemeSchema and schema-less with LDAP viewsyesyes
Typing infopredefined data types such as float or dateoptionalNumeric data onlyyesyes
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 indexesyesnonoyes
SQL infoSupport of SQLnonoSQL-like DML and DDL statementsyes
APIs and other access methodsLDAPRESTful HTTP APIJDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesAll languages with LDAP bindingsC++
Go
Java
Python
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresnononoyes
Triggersyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesSharding infocell divisionShardingyes, utilizing Spark Core
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 ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic execution of specific operationsnonoyes
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.yesnonono
User concepts infoAccess controlLDAP bind authenticationnonofine grained access rights according to SQL-standard

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More resources
Atos Standard Common RepositoryMilvusSpark SQLTransbase
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