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DBMS > Spark SQL vs. SWC-DB vs. Tibero vs. Vitess

System Properties Comparison Spark SQL vs. SWC-DB vs. Tibero vs. Vitess

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonSWC-DB infoSuper Wide Column Database  Xexclude from comparisonTibero  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionSpark SQL is a component on top of 'Spark Core' for structured data processingA high performance, scalable Wide Column DBMSA secure RDBMS, designed for easy portability from OracleScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSWide column storeRelational DBMSRelational DBMS
Secondary database modelsTime Series DBMSDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.08
Rank#364  Overall
#13  Wide column stores
Score1.59
Rank#148  Overall
#68  Relational DBMS
Score0.88
Rank#203  Overall
#95  Relational DBMS
Websitespark.apache.org/­sqlgithub.com/­kashirin-alex/­swc-db
www.swcdb.org
us.tmaxsoft.com/­products/­tiberovitess.io
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmltechnet.tmaxsoft.com/­upload/­download/­online/­tibero/­pver-20150504-000002/­index.htmlvitess.io/­docs
DeveloperApache Software FoundationAlex KashirinTmaxSoftThe Linux Foundation, PlanetScale
Initial release2014202020032013
Current release3.5.0 ( 2.13), September 20230.5, April 20216, April 201515.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoGPL V3commercialOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC++C and AssemblerGo
Server operating systemsLinux
OS X
Windows
LinuxAIX
HP-UX
Linux
Solaris
Windows
Docker
Linux
macOS
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes
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.nonoyes
Secondary indexesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query languageyesyes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
Proprietary protocol
Thrift
JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)
Tibero CLI
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesJava
Python
R
Scala
C++C
C#
C++
Cobol
Java
Objective-C
Perl
PHP
Python
Ruby
Visual Basic
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresnonoPersistent Stored Procedure (PSM)yes infoproprietary syntax
Triggersnonoyesyes
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreShardinghorizontal partitioning infoby range, hash, list or compositeSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency across shards
Immediate Consistency within a shard
Foreign keys infoReferential integritynoyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infotable locks or row locks depending on storage engine
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.nonono infoplanned for next versionyes
User concepts infoAccess controlnofine grained access rights according to SQL-standard (SQL 92, SQL 99)Users with fine-grained authorization concept infono user groups or roles

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More resources
Spark SQLSWC-DB infoSuper Wide Column DatabaseTiberoVitess
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