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DBMS > Apache Impala vs. Greenplum vs. Kinetica

System Properties Comparison Apache Impala vs. Greenplum vs. Kinetica

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonGreenplum  Xexclude from comparisonKinetica  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.Fully vectorized database across both GPUs and CPUs
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score8.37
Rank#48  Overall
#30  Relational DBMS
Score0.64
Rank#236  Overall
#109  Relational DBMS
Websiteimpala.apache.orggreenplum.orgwww.kinetica.com
Technical documentationimpala.apache.org/­impala-docs.htmldocs.greenplum.orgdocs.kinetica.com
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaPivotal Software Inc.Kinetica
Initial release201320052012
Current release4.1.0, June 20227.0.0, September 20237.1, August 2021
License infoCommercial or Open SourceOpen Source infoApache Version 2Open Source infoApache 2.0commercial
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++
Server operating systemsLinuxLinuxLinux
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.noyes infosince Version 4.2no
Secondary indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
JDBC
ODBC
RESTful HTTP API
Supported programming languagesAll languages supporting JDBC/ODBCC
Java
Perl
Python
R
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyesuser defined functions
Triggersnoyesyes infotriggers when inserted values for one or more columns fall within a specified range
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
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.nonoyes infoGPU vRAM or System RAM
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standardAccess rights for users and roles on table level

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More resources
Apache ImpalaGreenplumKinetica
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