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

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

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonSpark SQL  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsDatabase as a Service offering with high compatibility to Microsoft SQL ServerA Wide Column Store for rapid development using massive semi-structured datasetsSpark 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.
Primary database modelRelational DBMSRelational DBMSWide column storeRelational 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
Score4.48
Rank#75  Overall
#6  Wide column stores
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/­databaseazure.microsoft.com/­en-us/­services/­storage/­tablesspark.apache.org/­sqlwww.tencentcloud.com/­products/­dcdb
Technical documentationdocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­azure-sqlspark.apache.org/­docs/­latest/­sql-programming-guide.htmlwww.tencentcloud.com/­document/­product/­1042
DeveloperKineticaMicrosoftMicrosoftApache Software FoundationTencent
Initial release20122010201220142013
Current release7.1, August 2021V123.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud servicenoyesyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C++Scala
Server operating systemsLinuxhostedhostedLinux
OS X
Windows
hosted
Data schemeyesyesschema-freeyesyes
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 indexesyesyesnonoyes
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnoSQL-like DML and DDL statementsyes
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
RESTful HTTP APIJDBC
ODBC
JDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
C
C#
C++
Java
PHP
Python
Ruby
Server-side scripts infoStored proceduresuser defined functionsTransact SQLnonoyes
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyesnonoyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceyes, utilizing Spark CoreAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes, with always 3 replicas availableyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.noneMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDoptimistic lockingnoACID
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-standardAccess rights based on private key authentication or shared access signaturesnoUsers with fine-grained authorization concept

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More resources
KineticaMicrosoft Azure SQL Database infoformerly SQL AzureMicrosoft Azure Table StorageSpark SQLTDSQL for MySQL
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