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DBMS > Spark SQL vs. Tkrzw vs. Trafodion vs. Valentina Server

System Properties Comparison Spark SQL vs. Tkrzw vs. Trafodion vs. Valentina Server

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonTrafodion  Xexclude from comparisonValentina Server  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionSpark SQL is a component on top of 'Spark Core' for structured data processingA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto CabinetTransactional SQL-on-Hadoop DBMSObject-relational database and reports server
Primary database modelRelational DBMSKey-value storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.07
Rank#372  Overall
#57  Key-value stores
Score0.21
Rank#325  Overall
#144  Relational DBMS
Websitespark.apache.org/­sqldbmx.net/­tkrzwtrafodion.apache.orgwww.valentina-db.net
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmltrafodion.apache.org/­documentation.htmlvalentina-db.com/­docs/­dokuwiki/­v5/­doku.php
DeveloperApache Software FoundationMikio HirabayashiApache Software Foundation, originally developed by HPParadigma Software
Initial release2014202020141999
Current release3.5.0 ( 2.13), September 20230.9.3, August 20202.3.0, February 20195.7.5
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC++C++, Java
Server operating systemsLinux
OS X
Windows
Linux
macOS
LinuxLinux
OS X
Windows
Data schemeyesschema-freeyesyes
Typing infopredefined data types such as float or dateyesnoyesyes
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 statementsnoyesyes
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
ODBC
Supported programming languagesJava
Python
R
Scala
C++
Java
Python
Ruby
All languages supporting JDBC/ODBC/ADO.Net.Net
C
C#
C++
Objective-C
PHP
Ruby
Visual Basic
Visual Basic.NET
Server-side scripts infoStored proceduresnonoJava Stored Proceduresyes
Triggersnononoyes
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CorenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneyes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infovia user defined functions and HBaseno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
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.noyes infousing specific database classesnoyes
User concepts infoAccess controlnonofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Spark SQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetTrafodionValentina Server
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