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DBMS > Datomic vs. Spark SQL vs. STSdb vs. Valentina Server

System Properties Comparison Datomic vs. Spark SQL vs. STSdb vs. Valentina Server

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Editorial information provided by DB-Engines
NameDatomic  Xexclude from comparisonSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilitySpark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodObject-relational database and reports server
Primary database modelRelational DBMSRelational DBMSKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.04
Rank#360  Overall
#52  Key-value stores
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websitewww.datomic.comspark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4www.valentina-db.net
Technical documentationdocs.datomic.comspark.apache.org/­docs/­latest/­sql-programming-guide.htmlvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperCognitectApache Software FoundationSTS Soft SCParadigma Software
Initial release2012201420111999
Current release1.0.6735, June 20233.5.0 ( 2.13), September 20234.0.8, September 20155.7.5
License infoCommercial or Open Sourcecommercial infolimited edition freeOpen Source infoApache 2.0Open Source infoGPLv2, commercial license availablecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, ClojureScalaC#
Server operating systemsAll OS with a Java VMLinux
OS X
Windows
WindowsLinux
OS X
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyes infoprimitive types and user defined types (classes)yes
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.nono
Secondary indexesyesnonoyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsnoyes
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
.NET Client APIODBC
Supported programming languagesClojure
Java
Java
Python
R
Scala
C#
Java
.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresyes infoTransaction Functionsnonoyes
TriggersBy using transaction functionsnonoyes
Partitioning methods infoMethods for storing different data on different nodesnone infoBut extensive use of caching in the application peersyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoBut extensive use of caching in the application peersnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes inforecommended only for testing and developmentnoyes
User concepts infoAccess controlnononofine grained access rights according to SQL-standard

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More resources
DatomicSpark SQLSTSdbValentina Server
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