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DBMS > Spark SQL vs. Splunk vs. Tkrzw vs. Yaacomo

System Properties Comparison Spark SQL vs. Splunk vs. Tkrzw vs. Yaacomo

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonSplunk  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionSpark SQL is a component on top of 'Spark Core' for structured data processingAnalytics Platform for Big DataA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto CabinetOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSSearch engineKey-value storeRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score86.45
Rank#14  Overall
#2  Search engines
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitespark.apache.org/­sqlwww.splunk.comdbmx.net/­tkrzwyaacomo.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.splunk.com/­Documentation/­Splunk
DeveloperApache Software FoundationSplunk Inc.Mikio HirabayashiQ2WEB GmbH
Initial release2014200320202009
Current release3.5.0 ( 2.13), September 20230.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infoLimited free edition and free developer edition availableOpen Source infoApache Version 2.0commercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaC++
Server operating systemsLinux
OS X
Windows
Linux
OS X
Solaris
Windows
Linux
macOS
Android
Linux
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnoyes
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.noyesnono
Secondary indexesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsno infoSplunk Search Processing Language for search commandsnoyes
APIs and other access methodsJDBC
ODBC
HTTP RESTJDBC
ODBC
Supported programming languagesJava
Python
R
Scala
C#
Java
JavaScript
PHP
Python
Ruby
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnoyesno
Triggersnoyesnoyes
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreShardingnonehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono infoA 'Transaction' in Splunk has a different meaning: grouping related events into a single one for later searchingACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nonoyes infousing specific database classesyes
User concepts infoAccess controlnoAccess rights for users and rolesnofine grained access rights according to SQL-standard

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More resources
Spark SQLSplunkTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetYaacomo
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