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DBMS > Spark SQL vs. Sphinx vs. Tkrzw vs. ToroDB

System Properties Comparison Spark SQL vs. Sphinx vs. Tkrzw vs. ToroDB

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparisonTkrzw infoSuccessor of Tokyo Cabinet and Kyoto Cabinet  Xexclude from comparisonToroDB  Xexclude from comparison
ToroDB seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionSpark SQL is a component on top of 'Spark Core' for structured data processingOpen source search engine for searching in data from different sources, e.g. relational databasesA concept of libraries, allowing an application program to store and query key-value pairs in a file. Successor of Tokyo Cabinet and Kyoto CabinetA MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelRelational DBMSSearch engineKey-value storeDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Score0.00
Rank#383  Overall
#60  Key-value stores
Websitespark.apache.org/­sqlsphinxsearch.comdbmx.net/­tkrzwgithub.com/­torodb/­server
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docs
DeveloperApache Software FoundationSphinx Technologies Inc.Mikio Hirabayashi8Kdata
Initial release2014200120202016
Current release3.5.0 ( 2.13), September 20233.5.1, February 20230.9.3, August 2020
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availableOpen Source infoApache Version 2.0Open Source infoAGPL-V3
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
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Linux
macOS
All OS with a Java 7 VM
Data schemeyesyesschema-freeschema-free
Typing infopredefined data types such as float or dateyesnonoyes infostring, integer, double, boolean, date, object_id
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 indexesnoyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (SphinxQL)no
APIs and other access methodsJDBC
ODBC
Proprietary protocol
Supported programming languagesJava
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C++
Java
Python
Ruby
Server-side scripts infoStored proceduresnonono
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supportednoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnonenonenoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Sphinx index.yesyes
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 controlnononoAccess rights for users and roles

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More resources
Spark SQLSphinxTkrzw infoSuccessor of Tokyo Cabinet and Kyoto CabinetToroDB
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