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DBMS > Cubrid vs. Spark SQL vs. Teradata

System Properties Comparison Cubrid vs. Spark SQL vs. Teradata

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Editorial information provided by DB-Engines
NameCubrid  Xexclude from comparisonSpark SQL  Xexclude from comparisonTeradata  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)
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.44
Rank#168  Overall
#77  Relational DBMS
Score19.56
Rank#34  Overall
#21  Relational DBMS
Score48.95
Rank#20  Overall
#14  Relational DBMS
Websitecubrid.com (korean)
cubrid.org (english)
spark.apache.org/­sqlwww.teradata.com
Technical documentationcubrid.org/­manualsspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.teradata.com
DeveloperCUBRID Corporation, CUBRID FoundationApache Software FoundationTeradata
Initial release200820141984
Current release11.0, January 20213.5.0 ( 2.13), September 2023Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache Version 2.0Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC, C++, JavaScala
Server operating systemsLinux
Windows
Linux
OS X
Windows
hosted
Linux
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.nonoyes
Secondary indexesyesnoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash index
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyes infoSQL 2016 + extensions
APIs and other access methodsADO.NET
JDBC
ODBC
OLE DB
JDBC
ODBC
.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
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
Server-side scripts infoStored proceduresJava Stored Proceduresnoyes infoUDFs, stored procedures, table functions in parallel
Triggersyesnoyes
Partitioning methods infoMethods for storing different data on different nodesnoneyes, utilizing Spark CoreSharding infoHashing
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneMulti-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 ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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 controlfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standard

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More resources
CubridSpark SQLTeradata
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