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DBMS > Greenplum vs. Oracle Berkeley DB vs. Spark SQL vs. Transbase vs. Yanza

System Properties Comparison Greenplum vs. Oracle Berkeley DB vs. Spark SQL vs. Transbase vs. Yanza

Editorial information provided by DB-Engines
NameGreenplum  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded 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.Widely used in-process key-value storeSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMSTime Series DBMS for IoT Applications
Primary database modelRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Relational DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score8.37
Rank#48  Overall
#30  Relational DBMS
Score2.21
Rank#117  Overall
#20  Key-value stores
#3  Native XML DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websitegreenplum.orgwww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.htmlyanza.com
Technical documentationdocs.greenplum.orgdocs.oracle.com/­cd/­E17076_05/­html/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperPivotal Software Inc.Oracle infooriginally developed by Sleepycat, which was acquired by OracleApache Software FoundationTransaction Software GmbHYanza
Initial release20051994201419872015
Current release7.0.0, September 202318.1.40, May 20203.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infocommercial license availableOpen Source infoApache 2.0commercial infofree development licensecommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenonononono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, Java, C++ (depending on the Berkeley DB edition)ScalaC and C++
Server operating systemsLinuxAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Windows
Data schemeyesschema-freeyesyesschema-free
Typing infopredefined data types such as float or dateyesnoyesyesno
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 4.2yes infoonly with the Berkeley DB XML editionnonono
Secondary indexesyesyesnoyesno
SQL infoSupport of SQLyesyes infoSQL interfaced based on SQLite is availableSQL-like DML and DDL statementsyesno
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
HTTP API
Supported programming languagesC
Java
Perl
Python
R
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
any language that supports HTTP calls
Server-side scripts infoStored proceduresyesnonoyesno
Triggersyesyes infoonly for the SQL APInoyesyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesShardingnoneyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationnoneSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDnoyesno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardnonofine grained access rights according to SQL-standardno

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More resources
GreenplumOracle Berkeley DBSpark SQLTransbaseYanza
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