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

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

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonTransbase  Xexclude from comparisonYaacomo  Xexclude from comparisonYanza  Xexclude from comparison
Yaacomo seems to be discontinued and is removed from the DB-Engines rankingYanza 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 processingA resource-optimized, high-performance, universally applicable RDBMSOpenCL based in-memory RDBMS, designed for efficiently utilizing the hardware via parallel computingTime Series DBMS for IoT Applications
Primary database modelRelational DBMSRelational DBMSRelational DBMSTime Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.11
Rank#341  Overall
#150  Relational DBMS
Websitespark.apache.org/­sqlwww.transaction.de/­en/­products/­transbase.htmlyaacomo.comyanza.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.transaction.de/­en/­products/­transbase/­features.html
DeveloperApache Software FoundationTransaction Software GmbHQ2WEB GmbHYanza
Initial release2014198720092015
Current release3.5.0 ( 2.13), September 2023Transbase 8.3, 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial infofree development licensecommercialcommercial 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

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Implementation languageScalaC and C++
Server operating systemsLinux
OS X
Windows
FreeBSD
Linux
macOS
Solaris
Windows
Android
Linux
Windows
Windows
Data schemeyesyesyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.nononono
Secondary indexesnoyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyesno
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
Proprietary native API
JDBC
ODBC
HTTP API
Supported programming languagesJava
Python
R
Scala
C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python
any language that supports HTTP calls
Server-side scripts infoStored proceduresnoyesno
Triggersnoyesyesyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark Corehorizontal partitioningnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneSource-replica replicationSource-replica replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoyesACIDno
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.nonoyes
User concepts infoAccess controlnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standardno

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More resources
Spark SQLTransbaseYaacomoYanza
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