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DBMS > GBase vs. Postgres-XL vs. Spark SQL vs. Yanza

System Properties Comparison GBase vs. Postgres-XL vs. Spark SQL vs. Yanza

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Editorial information provided by DB-Engines
NameGBase  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSpark SQL  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionAn analytical database for business intelligence with large customers in China.Based on PostgreSQL enhanced with MPP and write-scale-out cluster featuresSpark SQL is a component on top of 'Spark Core' for structured data processingTime Series DBMS for IoT Applications
Primary database modelRelational DBMSRelational DBMSRelational DBMSTime Series DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.07
Rank#185  Overall
#86  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.gbase.cnwww.postgres-xl.orgspark.apache.org/­sqlyanza.com
Technical documentationwww.postgres-xl.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationYanza
Initial release2014 infosince 2012, originally named StormDB20142015
Current releaseGBase 8a10 R1, October 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoMozilla public licenseOpen Source infoApache 2.0commercial infofree version available
Cloud-based only infoOnly available as a cloud servicenononono 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 languageCScala
Server operating systemsLinux
macOS
Linux
OS X
Windows
Windows
Data schemeyesyesschema-free
Typing infopredefined data types such as float or dateyesyesno
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 infoXML type, but no XML query functionalitynono
Secondary indexesyesnono
SQL infoSupport of SQLyes infodistributed, parallel query executionSQL-like DML and DDL statementsno
APIs and other access methodsADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
HTTP API
Supported programming languages.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
any language that supports HTTP calls
Server-side scripts infoStored proceduresuser defined functionsnono
Triggersyesnoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningyes, utilizing Spark Corenone
Replication methods infoMethods for redundantly storing data on multiple nodesnonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACID infoMVCCnono
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 controlfine grained access rights according to SQL-standardnono

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More resources
GBasePostgres-XLSpark SQLYanza
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