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DBMS > Spark SQL vs. STSdb vs. Transbase vs. Yanza

System Properties Comparison Spark SQL vs. STSdb vs. Transbase vs. Yanza

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparisonTransbase  Xexclude from comparisonYanza  Xexclude from comparison
Yanza seems to be discontinued. Therefore it is excluded from the DB-Engines Ranking.
DescriptionSpark SQL is a component on top of 'Spark Core' for structured data processingKey-Value Store with special method for indexing infooptimized for high performance using a special indexing methodA resource-optimized, high-performance, universally applicable RDBMSTime Series DBMS for IoT Applications
Primary database modelRelational DBMSKey-value storeRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score19.15
Rank#33  Overall
#20  Relational DBMS
Score0.06
Rank#365  Overall
#55  Key-value stores
Score0.15
Rank#337  Overall
#147  Relational DBMS
Websitespark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4www.transaction.de/­en/­products/­transbase.htmlyanza.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperApache Software FoundationSTS Soft SCTransaction Software GmbHYanza
Initial release2014201119872015
Current release3.5.0 ( 2.13), September 20234.0.8, September 2015Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoGPLv2, commercial license availablecommercial infofree development licensecommercial 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 languageScalaC#C and C++
Server operating systemsLinux
OS X
Windows
WindowsFreeBSD
Linux
macOS
Solaris
Windows
Windows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyes infoprimitive types and user defined types (classes)yesno
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.nonono
Secondary indexesnonoyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyesno
APIs and other access methodsJDBC
ODBC
.NET Client APIADO.NET
JDBC
ODBC
Proprietary native API
HTTP API
Supported programming languagesJava
Python
R
Scala
C#
Java
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
any language that supports HTTP calls
Server-side scripts infoStored proceduresnonoyesno
Triggersnonoyesyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark Corenonenone
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoyesno
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.nono
User concepts infoAccess controlnonofine grained access rights according to SQL-standardno

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More resources
Spark SQLSTSdbTransbaseYanza
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