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DBMS > 4D vs. Greenplum vs. Spark SQL

System Properties Comparison 4D vs. Greenplum vs. Spark SQL

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Editorial information provided by DB-Engines
Name4D infoformer name: 4th Dimension  Xexclude from comparisonGreenplum  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionApplication development environment with integrated database management systemAnalytic 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.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score2.58
Rank#108  Overall
#54  Relational DBMS
Score8.37
Rank#48  Overall
#30  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.4d.comgreenplum.orgspark.apache.org/­sql
Technical documentationdeveloper.4d.comdocs.greenplum.orgspark.apache.org/­docs/­latest/­sql-programming-guide.html
Developer4D, IncPivotal Software Inc.Apache Software Foundation
Initial release198420052014
Current releasev20, April 20237.0.0, September 20233.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0Open 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 languageScala
Server operating systemsOS X
Windows
LinuxLinux
OS X
Windows
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.yesyes infosince Version 4.2no
Secondary indexesyesyesno
SQL infoSupport of SQLyes infoclose to SQL 92yesSQL-like DML and DDL statements
APIs and other access methodsODBC
RESTful HTTP API infoby using 4D Mobile
SOAP webservices
JDBC
ODBC
JDBC
ODBC
Supported programming languages4D proprietary IDE
PHP
C
Java
Perl
Python
R
Java
Python
R
Scala
Server-side scripts infoStored proceduresyesyesno
Triggersyesyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDno
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.nonono
User concepts infoAccess controlUsers and groupsfine grained access rights according to SQL-standardno

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More resources
4D infoformer name: 4th DimensionGreenplumSpark SQL
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