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DBMS > Kinetica vs. Microsoft Azure SQL Database vs. Spark SQL vs. TDSQL for MySQL vs. Trafodion

System Properties Comparison Kinetica vs. Microsoft Azure SQL Database vs. Spark SQL vs. TDSQL for MySQL vs. Trafodion

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonSpark 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.
DescriptionFully vectorized database across both GPUs and CPUsDatabase as a Service offering with high compatibility to Microsoft SQL ServerSpark 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 DBMSRelational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Graph DBMS
Spatial DBMS
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Score0.85
Rank#205  Overall
#95  Relational DBMS
Websitewww.kinetica.comazure.microsoft.com/­en-us/­products/­azure-sql/­databasespark.apache.org/­sqlwww.tencentcloud.com/­products/­dcdbtrafodion.apache.org
Technical documentationdocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­azure-sqlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.tencentcloud.com/­document/­product/­1042trafodion.apache.org/­documentation.html
DeveloperKineticaMicrosoftApache Software FoundationTencentApache Software Foundation, originally developed by HP
Initial release20122010201420132014
Current release7.1, August 2021V123.5.0 ( 2.13), September 20232.3.0, February 2019
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0commercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenoyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C++ScalaC++, Java
Server operating systemsLinuxhostedLinux
OS X
Windows
hostedLinux
Data schemeyesyesyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesyes
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.noyesnonono
Secondary indexesyesyesnoyesyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesSQL-like DML and DDL statementsyesyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
JDBC
ODBC
JDBC
ODBC
ADO.NET
JDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
C
C#
C++
Java
PHP
Python
Ruby
All languages supporting JDBC/ODBC/ADO.Net
Server-side scripts infoStored proceduresuser defined functionsTransact SQLnoyesJava Stored Procedures
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyesnoyesno
Partitioning methods infoMethods for storing different data on different nodesShardingyes, utilizing Spark CoreAutomatic shardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes, with always 3 replicas availablenoneMulti-source replication
Source-replica replication
yes, via HBase
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infovia user defined functions and HBase
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesnonoyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDnoACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMnonono
User concepts infoAccess controlAccess rights for users and roles on table levelfine grained access rights according to SQL-standardnoUsers with fine-grained authorization conceptfine grained access rights according to SQL-standard

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More resources
KineticaMicrosoft Azure SQL Database infoformerly SQL AzureSpark SQLTDSQL for MySQLTrafodion
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