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DBMS > Spark SQL vs. Transbase vs. Vitess

System Properties Comparison Spark SQL vs. Transbase vs. Vitess

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMSScalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.11
Rank#341  Overall
#150  Relational DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitespark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.htmlvitess.io
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.htmlvitess.io/­docs
DeveloperApache Software FoundationTransaction Software GmbHThe Linux Foundation, PlanetScale
Initial release201419872013
Current release3.5.0 ( 2.13), September 2023Transbase 8.3, 202215.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infofree development licenseOpen Source infoApache Version 2.0, commercial licenses available
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaC and C++Go
Server operating systemsLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Docker
Linux
macOS
Data schemeyesyesyes
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.nono
Secondary indexesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyes infowith proprietary extensions
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesJava
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
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 proceduresnoyesyes infoproprietary syntax
Triggersnoyesyes
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate 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 datanoyesACID at shard level
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engine
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.nonoyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardUsers with fine-grained authorization concept infono user groups or roles

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More resources
Spark SQLTransbaseVitess
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