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DBMS > Spark SQL vs. Teradata Aster vs. Yanza

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

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonTeradata Aster  Xexclude from comparisonYanza  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed from the DB-Engines ranking.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 processingPlatform for big data analytics on multistructured data sources and typesTime Series DBMS for IoT Applications
Primary database modelRelational 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
Websitespark.apache.org/­sqlyanza.com
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationTeradataYanza
Initial release201420052015
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialcommercial infofree version available
Cloud-based only infoOnly available as a cloud servicenonono infobut mainly used as a service provided by Yanza
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScala
Server operating systemsLinux
OS X
Windows
LinuxWindows
Data schemeyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Storeschema-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.noyes infoin Aster File Storeno
Secondary indexesnoyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsyesno
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
HTTP API
Supported programming languagesJava
Python
R
Scala
C
C#
C++
Java
Python
R
any language that supports HTTP calls
Server-side scripts infoStored proceduresnoR packagesno
Triggersnonoyes infoTimer and event based
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreShardingnone
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoDimension tables are replicated across all nodes in the cluster. The number of replicas for the file store can be configured.none
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoSQL Map-Reduce Frameworkno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate Consistency
Foreign keys infoReferential integritynonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
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 controlnofine grained access rights according to SQL-standardno

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More resources
Spark SQLTeradata AsterYanza
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