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DBMS > Apache Spark (SQL) vs. Greenplum

System Properties Comparison Apache Spark (SQL) vs. Greenplum

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Editorial information provided by DB-Engines
NameApache Spark (SQL)  Xexclude from comparisonGreenplum  Xexclude from comparison
DescriptionApache Spark SQL is a component on top of 'Spark Core' for structured data processingAnalytic 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 DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score21.62
Rank#29  Overall
#18  Relational DBMS
Score7.08
Rank#48  Overall
#30  Relational DBMS
Websitespark.apache.org/­sqlgreenplum.org
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.greenplum.org
DeveloperApache Software FoundationPivotal Software Inc.
Initial release20142005
Current release3.5.0 ( 2.13), September 20237.0.0, September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScala
Server operating systemsLinux
OS X
Windows
Linux
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyes
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 4.2
Secondary indexesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
Supported programming languagesJava
Python
R
Scala
C
Java
Perl
Python
R
Server-side scripts infoStored proceduresnoyes
Triggersnoyes
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nono
User concepts infoAccess controlnofine grained access rights according to SQL-standard

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More resources
Apache Spark (SQL)Greenplum
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