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DBMS > Spark SQL vs. Teradata Aster

System Properties Comparison Spark SQL vs. Teradata Aster

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonTeradata Aster  Xexclude from comparison
Teradata Aster has been integrated into other Teradata systems and therefore will be removed 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 types
Primary database modelRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score20.62
Rank#36  Overall
#22  Relational DBMS
Websitespark.apache.org/­sql
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperApache Software FoundationTeradata
Initial release20142005
Current release3.3.0 ( 2.13), June 2022
License infoCommercial or Open SourceOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScala
Server operating systemsLinux
OS X
Windows
Linux
Data schemeyesFlexible Schema (defined schema, partial schema, schema free) infodefined schema within the relational store; partial schema or schema free in the Aster File Store
Typing infopredefined data types such as float or dateyesyes
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 Store
Secondary indexesnoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
ADO.NET
JDBC
ODBC
OLE DB
Supported programming languagesJava
Python
R
Scala
C
C#
C++
Java
Python
R
Server-side scripts infoStored proceduresnoR packages
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreSharding
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.
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoSQL Map-Reduce Framework
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configuration
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
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-standard

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Spark SQLTeradata Aster
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