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

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

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonSTSdb  Xexclude from comparisonTeradata  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 hybrid cloud data analytics software platform (Teradata Vantage)Time Series DBMS for IoT Applications
Primary database modelRelational DBMSKey-value storeRelational DBMSTime Series DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
Time Series DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.04
Rank#33  Overall
#20  Relational DBMS
Score0.10
Rank#357  Overall
#51  Key-value stores
Score44.87
Rank#22  Overall
#15  Relational DBMS
Websitespark.apache.org/­sqlgithub.com/­STSSoft/­STSdb4www.teradata.comyanza.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.teradata.com
DeveloperApache Software FoundationSTS Soft SCTeradataYanza
Initial release2014201119842015
Current release3.5.0 ( 2.13), September 20234.0.8, September 2015Teradata Vantage 1.0 MU2, January 2019
License infoCommercial or Open SourceOpen Source infoApache 2.0Open Source infoGPLv2, commercial license availablecommercialcommercial 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#
Server operating systemsLinux
OS X
Windows
Windowshosted
Linux
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.noyesno
Secondary indexesnonoyes infoJoin-index to prejoin tables, aggregate index, sparse index, hash indexno
SQL infoSupport of SQLSQL-like DML and DDL statementsnoyes infoSQL 2016 + extensionsno
APIs and other access methodsJDBC
ODBC
.NET Client API.NET Client API
HTTP REST
JDBC
JMS Adapter
ODBC
OLE DB
HTTP API
Supported programming languagesJava
Python
R
Scala
C#
Java
C
C++
Cobol
Java (JDBC-ODBC)
Perl
PL/1
Python
R
Ruby
any language that supports HTTP calls
Server-side scripts infoStored proceduresnonoyes infoUDFs, stored procedures, table functions in parallelno
Triggersnonoyesyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CorenoneSharding infoHashingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnonenoneMulti-source replication
Source-replica replication
none
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 datanonoACIDno
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.noyes
User concepts infoAccess controlnonofine grained access rights according to SQL-standardno

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More resources
Spark SQLSTSdbTeradataYanza
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