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DBMS > Kinetica vs. Microsoft SQL Server vs. ObjectBox vs. Solr

System Properties Comparison Kinetica vs. Microsoft SQL Server vs. ObjectBox vs. Solr

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Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonMicrosoft SQL Server  Xexclude from comparisonObjectBox  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsMicrosofts flagship relational DBMSExtremely fast embedded database for small devices, IoT and MobileA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelRelational DBMSRelational DBMSObject oriented DBMSSearch engine
Secondary database modelsSpatial DBMS
Time Series DBMS
Document store
Graph DBMS
Spatial DBMS
Time Series DBMSSpatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.64
Rank#236  Overall
#109  Relational DBMS
Score824.29
Rank#3  Overall
#3  Relational DBMS
Score1.20
Rank#170  Overall
#5  Object oriented DBMS
Score42.91
Rank#24  Overall
#3  Search engines
Websitewww.kinetica.comwww.microsoft.com/­en-us/­sql-serverobjectbox.iosolr.apache.org
Technical documentationdocs.kinetica.comlearn.microsoft.com/­en-US/­sql/­sql-serverdocs.objectbox.iosolr.apache.org/­resources.html
DeveloperKineticaMicrosoftObjectBox LimitedApache Software Foundation
Initial release2012198920172006
Current release7.1, August 2021SQL Server 2022, November 20229.6.0, April 2024
License infoCommercial or Open Sourcecommercialcommercial inforestricted free version is availableOpen Source infoApache License 2.0Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud servicenononono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
SQLServer Flex @ STACKIT offers a managed version of SQL Server with adjustable CPU, RAM, storage amount and speed, in enterprise grade to perfectly match all application requirements. All services are 100% GDPR-compliant.
Implementation languageC, C++C++C and C++Java
Server operating systemsLinuxLinux
Windows
Android
iOS
Linux
macOS
Windows
All 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.noyesnoyes
Secondary indexesyesyesyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLSQL-like DML and DDL statementsyesnoSolr Parallel SQL Interface
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)
Proprietary native APIJava API
RESTful HTTP/JSON API
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic
C
C++
Dart
Go
Java
JavaScript infoplanned (as of Jan 2019)
Kotlin
Python infoplanned (as of Jan 2019)
Swift
.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 functionsTransact SQL, .NET languages, R, Python and (with SQL Server 2019) JavanoJava plugins
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyesnoyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesShardingtables can be distributed across several files (horizontal partitioning); sharding through federationnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes, but depending on the SQL-Server Editiononline/offline synchronization between client and serveryes
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 RAMyesnoyes
User concepts infoAccess controlAccess rights for users and roles on table levelfine grained access rights according to SQL-standardyesyes
More information provided by the system vendor
KineticaMicrosoft SQL ServerObjectBoxSolr
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More resources
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