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DBMS > Kinetica vs. Microsoft Azure SQL Database vs. Oracle Berkeley DB vs. SiteWhere vs. Sphinx

System Properties Comparison Kinetica vs. Microsoft Azure SQL Database vs. Oracle Berkeley DB vs. SiteWhere vs. Sphinx

Editorial information provided by DB-Engines
NameKinetica  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonOracle Berkeley DB  Xexclude from comparisonSiteWhere  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFully vectorized database across both GPUs and CPUsDatabase as a Service offering with high compatibility to Microsoft SQL ServerWidely used in-process key-value storeM2M integration platform for persisting/querying time series dataOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSRelational DBMSKey-value store infosupports sorted and unsorted key sets
Native XML DBMS infoin the Oracle Berkeley DB XML version
Time Series DBMSSearch engine
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
Score0.66
Rank#234  Overall
#107  Relational DBMS
Score76.78
Rank#16  Overall
#11  Relational DBMS
Score2.01
Rank#126  Overall
#21  Key-value stores
#3  Native XML DBMS
Score0.06
Rank#383  Overall
#43  Time Series DBMS
Score5.95
Rank#55  Overall
#5  Search engines
Websitewww.kinetica.comazure.microsoft.com/­en-us/­products/­azure-sql/­databasewww.oracle.com/­database/­technologies/­related/­berkeleydb.htmlgithub.com/­sitewhere/­sitewheresphinxsearch.com
Technical documentationdocs.kinetica.comdocs.microsoft.com/­en-us/­azure/­azure-sqldocs.oracle.com/­cd/­E17076_05/­html/­index.htmlsitewhere1.sitewhere.io/­index.htmlsphinxsearch.com/­docs
DeveloperKineticaMicrosoftOracle infooriginally developed by Sleepycat, which was acquired by OracleSiteWhereSphinx Technologies Inc.
Initial release20122010199420102001
Current release7.1, August 2021V1218.1.40, May 20203.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infocommercial license availableOpen Source infoCommon Public Attribution License Version 1.0Open Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC, C++C++C, Java, C++ (depending on the Berkeley DB edition)JavaC++
Server operating systemsLinuxhostedAIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows
Linux
OS X
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesschema-freepredefined schemeyes
Typing infopredefined data types such as float or dateyesyesnoyesno
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.noyesyes infoonly with the Berkeley DB XML editionno
Secondary indexesyesyesyesnoyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like DML and DDL statementsyesyes infoSQL interfaced based on SQLite is availablenoSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
RESTful HTTP API
ADO.NET
JDBC
ODBC
HTTP RESTProprietary protocol
Supported programming languagesC++
Java
JavaScript (Node.js)
Python
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net infoFigaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others infoThird-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js) info3rd party binding
Perl
Python
Tcl
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresuser defined functionsTransact SQLnono
Triggersyes infotriggers when inserted values for one or more columns fall within a specified rangeyesyes infoonly for the SQL APIno
Partitioning methods infoMethods for storing different data on different nodesShardingnoneSharding infobased on HBaseSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationyes, with always 3 replicas availableSource-replica replicationselectable replication factor infobased on HBasenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonononono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency depending on configurationImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityyesyesnonono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyesyesyesyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoGPU vRAM or System RAMyesno
User concepts infoAccess controlAccess rights for users and roles on table levelfine grained access rights according to SQL-standardnoUsers with fine-grained authorization conceptno

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More resources
KineticaMicrosoft Azure SQL Database infoformerly SQL AzureOracle Berkeley DBSiteWhereSphinx
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