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DBMS > Greenplum vs. Spark SQL vs. Transbase vs. Yaacomo

System Properties Comparison Greenplum vs. Spark SQL vs. Transbase vs. Yaacomo

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Editorial information provided by DB-Engines
NameGreenplum  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparisonYaacomo  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines ranking
DescriptionAnalytic 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 processingA resource-optimized, high-performance, universally applicable RDBMSOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computing
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.23
Rank#47  Overall
#30  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.15
Rank#337  Overall
#147  Relational DBMS
Websitegreenplum.orgspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.htmlyaacomo.com
Technical documentationdocs.greenplum.orgspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperPivotal Software Inc.Apache Software FoundationTransaction Software GmbHQ2WEB GmbH
Initial release2005201419872009
Current release7.0.0, September 20233.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoApache 2.0commercial infofree development licensecommercial
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScalaC and C++
Server operating systemsLinuxLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Android
Linux
Windows
Data schemeyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.yes infosince Version 4.2nonono
Secondary indexesyesnoyesyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyesyes
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
JDBC
ODBC
Supported programming languagesC
Java
Perl
Python
R
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyesnoyes
Triggersyesnoyesyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Corehorizontal partitioning
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneSource-replica replicationSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoyesACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.nononoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
GreenplumSpark SQLTransbaseYaacomo
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