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

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

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonKinetica  Xexclude from comparisonPostgres-XL  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopFully vectorized database across both GPUs and CPUsBased on PostgreSQL enhanced with MPP and write-scale-out cluster features
Primary database modelRelational DBMSRelational DBMSRelational DBMS
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
Score12.57
Rank#40  Overall
#24  Relational DBMS
Score0.51
Rank#253  Overall
#116  Relational DBMS
Score0.46
Rank#258  Overall
#120  Relational DBMS
Websiteimpala.apache.orgwww.kinetica.comwww.postgres-xl.org
Technical documentationimpala.apache.org/­impala-docs.htmldocs.kinetica.comwww.postgres-xl.org/­documentation
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaKinetica
Initial release201320122014 infosince 2012, originally named StormDB
Current release4.1.0, June 20227.1, August 202110 R1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2commercialOpen Source infoMozilla public license
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++C, C++C
Server operating systemsLinuxLinuxLinux
macOS
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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 functionality
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsSQL-like DML and DDL statementsyes infodistributed, parallel query execution
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
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
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceuser defined functionsuser defined functions
Triggersnoyes infotriggers when inserted values for one or more columns fall within a specified rangeyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardinghorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoACID infoMVCC
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoGPU vRAM or System RAMno
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-standard

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More resources
Apache ImpalaKineticaPostgres-XL
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