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DBMS > Apache Impala vs. Kinetica vs. Postgres-XL vs. SiriDB vs. Sphinx

System Properties Comparison Apache Impala vs. Kinetica vs. Postgres-XL vs. SiriDB vs. Sphinx

Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonKinetica  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSiriDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopFully vectorized database across both GPUs and CPUsBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresOpen 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 storeSpatial DBMS
Time Series DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score10.63
Rank#40  Overall
#24  Relational DBMS
Score0.42
Rank#261  Overall
#120  Relational DBMS
Score0.43
Rank#260  Overall
#119  Relational DBMS
Score0.00
Rank#385  Overall
#40  Time Series DBMS
Score5.97
Rank#56  Overall
#5  Search engines
Websiteimpala.apache.orgwww.kinetica.comwww.postgres-xl.orgsiridb.comsphinxsearch.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.kinetica.comwww.postgres-xl.org/­documentationdocs.siridb.comsphinxsearch.com/­docs
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaKineticaCesbitSphinx Technologies Inc.
Initial release201320122014 infosince 2012, originally named StormDB20172001
Current release4.1.0, June 20227.1, August 202110 R1, October 20183.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoMozilla public licenseOpen 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

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Implementation languageC++C, C++CCC++
Server operating systemsLinuxLinuxLinux
macOS
LinuxFreeBSD
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.nonoyes infoXML type, but no XML query functionalityno
Secondary indexesyesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsyes infodistributed, parallel query executionnoSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
HTTP APIProprietary protocol
Supported programming languagesAll languages supporting JDBC/ODBCC++
Java
JavaScript (Node.js)
Python
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsuser defined functionsnono
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyesnono
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioningShardingSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenononono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoMVCCnono
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.noyes infoGPU vRAM or System RAMnoyes
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and KerberosAccess rights for users and roles on table levelfine grained access rights according to SQL-standardsimple rights management via user accountsno

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More resources
Apache ImpalaKineticaPostgres-XLSiriDBSphinx
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