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DBMS > Kinetica vs. Linter vs. Microsoft Azure SQL Database vs. Solr

System Properties Comparison Kinetica vs. Linter vs. Microsoft Azure SQL Database vs. Solr

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonLinter  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsRDBMS for high security requirementsDatabase as a Service offering with high compatibility to Microsoft SQL ServerA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSRelational DBMSRelational DBMSSearch engine
Secondary database modelsSpatial DBMS
Time Series DBMS
Spatial DBMSDocument store
Graph DBMS
Spatial DBMS
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score0.12
Rank#350  Overall
#152  Relational DBMS
Score76.78
Rank#16  Overall
#11  Relational DBMS
Score41.02
Rank#24  Overall
#3  Search engines
Websitewww.kinetica.comlinter.ruazure.microsoft.com/­en-us/­products/­azure-sql/­databasesolr.apache.org
Technical documentationdocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­azure-sqlsolr.apache.org/­resources.html
DeveloperKineticarelex.ruMicrosoftApache Software Foundation
Initial release2012199020102006
Current release7.1, August 2021V129.6.1, May 2024
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoApache Version 2
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 and C++C++Java
Server operating systemsLinuxAIX
Android
BSD
HP Open VMS
iOS
Linux
OS X
VxWorks
Windows
hostedAll OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeyesyesyesyes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyesyesyes infosupports customizable data types and automatic typing
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.nonoyesyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyesSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
LINQ
ODBC
OLE DB
Oracle Call Interface (OCI)
ADO.NET
JDBC
ODBC
Java API
RESTful HTTP/JSON API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C
C#
C++
Java
Perl
PHP
Python
Qt
Ruby
Tcl
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresuser defined functionsyes infoproprietary syntax with the possibility to convert from PL/SQLTransact SQLJava plugins
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyesyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationSource-replica replicationyes, with always 3 replicas availableyes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononospark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integrityyesyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDoptimistic locking
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
User concepts infoAccess controlAccess rights for users and roles on table levelfine grained access rights according to SQL-standardfine grained access rights according to SQL-standardyes

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More resources
KineticaLinterMicrosoft Azure SQL Database infoformerly SQL AzureSolr
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