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DBMS > Kinetica vs. MarkLogic vs. Microsoft Azure SQL Database vs. Spark SQL

System Properties Comparison Kinetica vs. MarkLogic vs. Microsoft Azure SQL Database vs. Spark SQL

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonMarkLogic  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsOperational and transactional Enterprise NoSQL databaseDatabase as a Service offering with high compatibility to Microsoft SQL ServerSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelRelational DBMSDocument store
Native XML DBMS
RDF store infoas of version 7
Search engine
Relational DBMSRelational DBMS
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Graph DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score5.92
Rank#58  Overall
#10  Document stores
#1  Native XML DBMS
#1  RDF stores
#6  Search engines
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websitewww.kinetica.comwww.marklogic.comazure.microsoft.com/­en-us/­products/­azure-sql/­databasespark.apache.org/­sql
Technical documentationdocs.kinetica.comdocs.marklogic.comdocs.microsoft.com/­en-us/­azure/­azure-sqlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperKineticaMarkLogic Corp.MicrosoftApache Software Foundation
Initial release2012200120102014
Current release7.1, August 202111.0, December 2022V123.5.0 ( 2.13), September 2023
License infoCommercial or Open Sourcecommercialcommercial inforestricted free version is availablecommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenonoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C++C++Scala
Server operating systemsLinuxLinux
OS X
Windows
hostedLinux
OS X
Windows
Data schemeyesschema-free infoSchema can be enforcedyesyes
Typing infopredefined data types such as float or dateyesyesyesyes
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.noyesyesno
Secondary indexesyesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsyes infoSQL92yesSQL-like DML and DDL statements
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
Java API
Node.js Client API
ODBC
proprietary Optic API infoProprietary Query API, introduced with version 9
RESTful HTTP API
SPARQL
WebDAV
XDBC
XQuery
XSLT
ADO.NET
JDBC
ODBC
JDBC
ODBC
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java
Python
R
Scala
Server-side scripts infoStored proceduresuser defined functionsyes infovia XQuery or JavaScriptTransact SQLno
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyesno
Partitioning methods infoMethods for storing different data on different nodesShardingShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyesyes, with always 3 replicas availablenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infovia Hadoop Connector, HDFS Direct Access and in-database MapReduce jobsno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesnoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACID infocan act as a resource manager in an XA/JTA transactionACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyes, with Range Indexesno
User concepts infoAccess controlAccess rights for users and roles on table levelRole-based access control at the document and subdocument levelsfine grained access rights according to SQL-standardno

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More resources
KineticaMarkLogicMicrosoft Azure SQL Database infoformerly SQL AzureSpark SQL
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