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DBMS > Cubrid vs. Spark SQL vs. Teradata vs. Vitess

System Properties Comparison Cubrid vs. Spark SQL vs. Teradata vs. Vitess

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Editorial information provided by DB-Engines
NameCubrid  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata  Xexclude from comparisonVitess  Xexclude from comparison
DescriptionCUBRID is an open-source SQL-based relational database management system with object extensions for OLTPSpark SQL is a component on top of 'Spark Core' for structured data processingA hybrid cloud data analytics software platform (Teradata Vantage)Scalable, distributed, cloud-native DBMS, extending MySQL
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.20
Rank#169  Overall
#78  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score45.33
Rank#21  Overall
#15  Relational DBMS
Score0.82
Rank#209  Overall
#97  Relational DBMS
Websitecubrid.com (korean)
cubrid.org (english)
spark.apache.org/­sqlwww.teradata.comvitess.io
Technical documentationcubrid.org/­manualsspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.teradata.comvitess.io/­docs
DeveloperCUBRID Corporation, CUBRID FoundationApache Software FoundationTeradataThe Linux Foundation, PlanetScale
Initial release2008201419842013
Current release11.0, January 20213.5.0 ( 2.13), September 2023Teradata Vantage 1.0 MU2, January 201915.0.2, December 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercialOpen 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 languageC, C++, JavaScalaGo
Server operating systemsLinux
Windows
Linux
OS X
Windows
hosted
Linux
Docker
Linux
macOS
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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 indexesyesnoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash indexyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyes infoSQL 2016 + extensionsyes infowith proprietary extensions
APIs and other access methodsADO.NET
JDBC
ODBC
OLE DB
JDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
ADO.NET
JDBC
MySQL protocol
ODBC
Supported programming languagesC
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
Java
Python
R
Scala
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
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 proceduresJava Stored Proceduresnoyes infoUDFs, stored procedures, table functions in parallelyes infoproprietary syntax
Triggersyesnoyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark CoreSharding infoHashingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneMulti-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 integrityyesnoyesyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACIDACID 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.nonoyesyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standardUsers with fine-grained authorization concept infono user groups or roles

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More resources
CubridSpark SQLTeradataVitess
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