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DBMS > Amazon Redshift vs. Apache Impala vs. Greenplum

System Properties Comparison Amazon Redshift vs. Apache Impala vs. Greenplum

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Editorial information provided by DB-Engines
NameAmazon Redshift  Xexclude from comparisonApache Impala  Xexclude from comparisonGreenplum  Xexclude from comparison
DescriptionLarge scale data warehouse service for use with business intelligence toolsAnalytic 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.
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument storeDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score20.63
Rank#33  Overall
#20  Relational DBMS
Score15.06
Rank#39  Overall
#24  Relational DBMS
Score9.20
Rank#48  Overall
#30  Relational DBMS
Websiteaws.amazon.com/­redshiftimpala.apache.orggreenplum.org
Technical documentationdocs.aws.amazon.com/­redshiftimpala.apache.org/­impala-docs.htmldocs.greenplum.org
DeveloperAmazon (based on PostgreSQL)Apache Software Foundation infoApache top-level project, originally developed by ClouderaPivotal Software Inc.
Initial release201220132005
Current release4.1.0, June 20227.0.0, September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++
Server operating systemshostedLinuxLinux
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 infosince Version 4.2
Secondary indexesrestrictedyesyes
SQL infoSupport of SQLyes infodoes not fully support an SQL-standardSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
JDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCAll languages supporting JDBC/ODBCC
Java
Perl
Python
R
Server-side scripts infoStored proceduresuser defined functions infoin Pythonyes infouser defined functions and integration of map-reduceyes
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyesselectable replication factorSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyes infoinformational only, not enforced by the systemnoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoACID
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.yesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosfine grained access rights according to SQL-standard

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More resources
Amazon RedshiftApache ImpalaGreenplum
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