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DBMS > Citus vs. Impala vs. Kinetica vs. SiriDB vs. Sphinx

System Properties Comparison Citus vs. Impala vs. Kinetica vs. SiriDB vs. Sphinx

Editorial information provided by DB-Engines
NameCitus  Xexclude from comparisonImpala  Xexclude from comparisonKinetica  Xexclude from comparisonSiriDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionScalable hybrid operational and analytics RDBMS for big data use cases based on PostgreSQLAnalytic DBMS for HadoopFully vectorized database across both GPUs and CPUsOpen Source Time Series DBMSOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSRelational DBMSRelational DBMSTime Series DBMSSearch engine
Secondary database modelsDocument storeDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.52
Rank#139  Overall
#68  Relational DBMS
Score18.71
Rank#38  Overall
#23  Relational DBMS
Score0.74
Rank#202  Overall
#99  Relational DBMS
Score0.01
Rank#347  Overall
#34  Time Series DBMS
Score8.01
Rank#56  Overall
#6  Search engines
Websitewww.citusdata.comwww.cloudera.com/­products/­open-source/­apache-hadoop/­impala.htmlwww.kinetica.comsiridb.netsphinxsearch.com
Technical documentationdocs.citusdata.comdocs.cloudera.com/­documentation/­enterprise/­latest/­topics/­impala.htmlwww.kinetica.com/­docsdocs.siridb.netsphinxsearch.com/­docs
DeveloperClouderaKineticaTransceptor TechnologySphinx Technologies Inc.
Initial release20102013201220172001
Current release8.1, December 20183.4.0, April 20207.1, August 20213.4.1, July 2021
License infoCommercial or Open SourceOpen Source infoAGPL, commercial license also availableOpen Source infoApache Version 2commercialOpen Source infoMIT LicenseOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenonononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageCC++C, C++CC++
Server operating systemsLinuxLinuxLinuxLinuxFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes infoNumeric datano
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.yes infospecific XML type available, but no XML query functionalitynonono
Secondary indexesyesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLyes infostandard, with numerous extensionsSQL-like DML and DDL statementsSQL-like DML and DDL statementsnoSQL-like query language (SphinxQL)
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
JDBC
ODBC
RESTful HTTP API
HTTP APIProprietary protocol
Supported programming languages.Net
C
C++
Delphi
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
All languages supporting JDBC/ODBCC++
Java
JavaScript (Node.js)
Python
C
C++
Go
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.yes infouser defined functions and integration of map-reduceuser defined functionsnono
Triggersyesnoyes infotriggers when inserted values for one or more columns fall within a specified rangenono
Partitioning methods infoMethods for storing different data on different nodesShardingShardingShardingShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replication infoother methods possible by using 3rd party extensionsselectable replication factorSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReducenonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integrityyesnoyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnononono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes 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.nonoyes infoGPU vRAM or System RAMyes
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users and roles on table levelsimple rights management via user accountsno
More information provided by the system vendor
CitusImpalaKineticaSiriDBSphinx
Specific characteristicsNative and fully vectorized database across both GPUs and CPUs, with memory first...
» more
Competitive advantagesBest in class geospatial and temporal analytics. Lockless architecture provides real-time...
» more
Typical application scenariosAny application requiring (1) real time insights, (2) time series analysis (3) geospatial...
» more
Key customersCitibank, US Air Force, Softbank, OVO, Telkomsel, USPS, 2 of the top 3 US Telcos,...
» more
Market metricsThe largest IoT deployment in the world, NORAD, runs on Kinetica.
» more
Licensing and pricing modelsAlways Free Tier in the Cloud, Pay-As-You-Go Consumption Based Pricing, and Portable...
» more

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More resources
CitusImpalaKineticaSiriDBSphinx
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