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DBMS > Apache Impala vs. Datomic vs. Greenplum

System Properties Comparison Apache Impala vs. Datomic vs. Greenplum

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Editorial information provided by DB-Engines
NameApache Impala  Xexclude from comparisonDatomic  Xexclude from comparisonGreenplum  Xexclude from comparison
DescriptionAnalytic DBMS for HadoopDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityAnalytic 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
Score13.77
Rank#40  Overall
#24  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score8.37
Rank#48  Overall
#30  Relational DBMS
Websiteimpala.apache.orgwww.datomic.comgreenplum.org
Technical documentationimpala.apache.org/­impala-docs.htmldocs.datomic.comdocs.greenplum.org
DeveloperApache Software Foundation infoApache top-level project, originally developed by ClouderaCognitectPivotal Software Inc.
Initial release201320122005
Current release4.1.0, June 20221.0.6735, June 20237.0.0, September 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2commercial infolimited edition freeOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java, Clojure
Server operating systemsLinuxAll OS with a Java VMLinux
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 indexesyesyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP APIJDBC
ODBC
Supported programming languagesAll languages supporting JDBC/ODBCClojure
Java
C
Java
Perl
Python
R
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceyes infoTransaction Functionsyes
TriggersnoBy using transaction functionsyes
Partitioning methods infoMethods for storing different data on different nodesShardingnone infoBut extensive use of caching in the application peersSharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factornone infoBut extensive use of caching in the application peersSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReducenoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes inforecommended only for testing and developmentno
User concepts infoAccess controlAccess rights for users, groups and roles infobased on Apache Sentry and Kerberosnofine grained access rights according to SQL-standard

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More resources
Apache ImpalaDatomicGreenplum
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