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DBMS > Spark SQL vs. SQLite vs. SWC-DB vs. Valentina Server

System Properties Comparison Spark SQL vs. SQLite vs. SWC-DB vs. Valentina Server

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonSQLite  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparisonValentina Server  Xexclude from comparison
DescriptionSpark SQL is a component on top of 'Spark Core' for structured data processingWidely used embeddable, in-process RDBMSA high performance, scalable Wide Column DBMSObject-relational database and reports server
Primary database modelRelational DBMSRelational DBMSWide column storeRelational DBMS
Secondary database modelsTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score114.32
Rank#10  Overall
#7  Relational DBMS
Score0.01
Rank#376  Overall
#13  Wide column stores
Score0.17
Rank#327  Overall
#145  Relational DBMS
Websitespark.apache.org/­sqlwww.sqlite.orggithub.com/­kashirin-alex/­swc-db
www.swcdb.org
www.valentina-db.net
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.sqlite.org/­docs.htmlvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperApache Software FoundationDwayne Richard HippAlex KashirinParadigma Software
Initial release2014200020201999
Current release3.5.0 ( 2.13), September 20233.45.3  (15 April 2024), April 20240.5, April 20215.7.5
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoPublic DomainOpen Source infoGPL V3commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaCC++
Server operating systemsLinux
OS X
Windows
server-lessLinuxLinux
OS X
Windows
Data schemeyesyes infodynamic column typesschema-freeyes
Typing infopredefined data types such as float or dateyesyes infonot rigid because of 'dynamic typing' concept.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.nonono
Secondary indexesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infoSQL-92 is not fully supportedSQL-like query languageyes
APIs and other access methodsJDBC
ODBC
ADO.NET infoinofficial driver
JDBC infoinofficial driver
ODBC infoinofficial driver
Proprietary protocol
Thrift
ODBC
Supported programming languagesJava
Python
R
Scala
Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl
C++.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresnononoyes
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CorenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyes infovia file-system locksyes
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.noyesnoyes
User concepts infoAccess controlnonofine grained access rights according to SQL-standard

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More resources
Spark SQLSQLiteSWC-DB infoSuper Wide Column DatabaseValentina Server
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