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DBMS > Kinetica vs. Sphinx

System Properties Comparison Kinetica vs. Sphinx

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionGPU-accelerated database for real-time analysis of large and streaming datasetsOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSSearch engine
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.53
Rank#199  Overall
#96  Relational DBMS
Score7.39
Rank#47  Overall
#5  Search engines
Websitewww.kinetica.comsphinxsearch.com
Technical documentationwww.kinetica.com/­docssphinxsearch.com/­docs
DeveloperKineticaSphinx Technologies Inc.
Initial release20122001
Current release6.03.1.1, October 2018
License infoCommercial or Open SourcecommercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C++
Server operating systemsLinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyes
Typing infopredefined data types such as float or dateyesno
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.no
Secondary indexesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like query language (SphinxQL)
APIs and other access methodsRESTful HTTP API
JDBC
ODBC
Proprietary protocol
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functionsno
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMaster-slave replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users and roles on table levelno

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More resources
KineticaSphinx
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Job opportunities

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