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DBMS > Spark SQL vs. TDSQL for MySQL vs. Trafodion

System Properties Comparison Spark SQL vs. TDSQL for MySQL vs. Trafodion

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Editorial information provided by DB-Engines
NameSpark SQL  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparisonTrafodion  Xexclude from comparison
Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.
DescriptionSpark SQL is a component on top of 'Spark Core' for structured data processingA high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.Transactional SQL-on-Hadoop DBMS
Primary database modelRelational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.85
Rank#205  Overall
#95  Relational DBMS
Websitespark.apache.org/­sqlwww.tencentcloud.com/­products/­dcdbtrafodion.apache.org
Technical documentationspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.tencentcloud.com/­document/­product/­1042trafodion.apache.org/­documentation.html
DeveloperApache Software FoundationTencentApache Software Foundation, originally developed by HP
Initial release201420132014
Current release3.5.0 ( 2.13), September 20232.3.0, February 2019
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageScalaC++, Java
Server operating systemsLinux
OS X
Windows
hostedLinux
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesyes
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 indexesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyes
APIs and other access methodsJDBC
ODBC
JDBC
ODBC
ADO.NET
JDBC
ODBC
Supported programming languagesJava
Python
R
Scala
C
C#
C++
Java
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresnoyesJava Stored Procedures
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesyes, utilizing Spark CoreAutomatic shardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-source replication
Source-replica replication
yes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACID
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.nonono
User concepts infoAccess controlnoUsers with fine-grained authorization conceptfine grained access rights according to SQL-standard

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More resources
Spark SQLTDSQL for MySQLTrafodion
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