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DBMS > Spark SQL vs. Tkrzw vs. YTsaurus

System Properties Comparison Spark SQL vs. Tkrzw vs. YTsaurus

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonYTsaurus  Xexclude from comparison
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 CabinetYTsaurus is an open source platform for distributed storage and processing.
Primary database modelRelational DBMSKey-value storeDocument store
Key-value store
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#324  Overall
#45  Document stores
#48  Key-value stores
Websitespark.apache.org/­sqldbmx.net/­tkrzwytsaurus.tech
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlytsaurus.tech/­docs/­en
DeveloperApache Software FoundationMikio HirabayashiYandex
Initial release201420202023
Current release3.5.0 ( 2.13), September 20230.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache Version 2.0Open Source infoApache License, Version 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC++C++
Server operating systemsLinux
OS X
Windows
Linux
macOS
Ubuntu
Data schemeyesschema-free
Typing infopredefined data types such as float or dateyesnoyes
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 indexesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoYQL, an SQL-based language, is supported
APIs and other access methodsJDBC
ODBC
Supported programming languagesJava
Python
R
Scala
C++
Java
Python
Ruby
C++
Go
Java
JavaScript
Python
Server-side scripts infoStored proceduresnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CorenoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynono
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 persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infousing specific database classes
User concepts infoAccess controlnonoAccess Control Lists

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More resources
Spark SQLTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetYTsaurus
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