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DBMS > Spark SQL vs. Sphinx vs. SQream DB vs. ToroDB

System Properties Comparison Spark SQL vs. Sphinx vs. SQream DB vs. ToroDB

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonSphinx  Xexclude from comparisonSQream DB  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 GPU-based, columnar RDBMS for big data analytics workloadsA MongoDB-compatible JSON document store, built on top of PostgreSQL
Primary database modelRelational DBMSSearch engineRelational DBMSDocument 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
Score0.70
Rank#227  Overall
#104  Relational DBMS
Websitespark.apache.org/­sqlsphinxsearch.comsqream.comgithub.com/­torodb/­server
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlsphinxsearch.com/­docsdocs.sqream.com
DeveloperApache Software FoundationSphinx Technologies Inc.SQream Technologies8Kdata
Initial release2014200120172016
Current release3.5.0 ( 2.13), September 20233.5.1, February 20232022.1.6, December 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoGPL version 2, commercial licence availablecommercialOpen 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++, CUDA, Haskell, Java, ScalaJava
Server operating systemsLinux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
LinuxAll OS with a Java 7 VM
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesnoyes, ANSI Standard SQL Typesyes 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.nono
Secondary indexesnoyes infofull-text index on all search fieldsno
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (SphinxQL)yes
APIs and other access methodsJDBC
ODBC
Proprietary protocol.Net
JDBC
ODBC
Supported programming languagesJava
Python
R
Scala
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnonouser defined functions in Python
Triggersnononono
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreSharding infoPartitioning is done manually, search queries against distributed index is supportedhorizontal and vertical partitioningSharding
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 datanonoACIDno
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.no
User concepts infoAccess controlnonoAccess rights for users and roles

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More resources
Spark SQLSphinxSQream DBToroDB
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