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DBMS > GBase vs. Netezza vs. Spark SQL vs. Transbase

System Properties Comparison GBase vs. Netezza vs. Spark SQL vs. Transbase

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Editorial information provided by DB-Engines
NameGBase  Xexclude from comparisonNetezza infoAlso called PureData System for Analytics by IBM  Xexclude from comparisonSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparison
DescriptionAn analytical database for business intelligence with large customers in China.Data warehouse and analytics appliance part of IBM PureSystemsSpark SQL is a component on top of 'Spark Core' for structured data processingA resource-optimized, high-performance, universally applicable RDBMS
Primary database modelRelational DBMSRelational DBMSRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.04
Rank#190  Overall
#88  Relational DBMS
Score10.18
Rank#46  Overall
#29  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.15
Rank#337  Overall
#147  Relational DBMS
Websitewww.gbase.cnwww.ibm.com/­products/­netezzaspark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.html
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperIBMApache Software FoundationTransaction Software GmbH
Initial release200020141987
Current releaseGBase 8a3.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercial infofree development license
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC and C++
Server operating systemsLinux infoincluded in applianceLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
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.nono
Secondary indexesyesnoyes
SQL infoSupport of SQLyesSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
OLE DB
JDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languagesC
C++
Fortran
Java
Lua
Perl
Python
R
Java
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
Server-side scripts infoStored proceduresyesnoyes
Triggersnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneSource-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoyes
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.nono
User concepts infoAccess controlUsers with fine-grained authorization conceptnofine grained access rights according to SQL-standard

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More resources
GBaseNetezza infoAlso called PureData System for Analytics by IBMSpark SQLTransbase
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