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DBMS > Microsoft Azure Search vs. OmniSci

System Properties Comparison Microsoft Azure Search vs. OmniSci

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Editorial information provided by DB-Engines
NameMicrosoft Azure Search  Xexclude from comparisonOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018  Xexclude from comparison
DescriptionSearch-as-a-service for web and mobile app developmentA high performance, in-memory, column-oriented RDBMS, designed to run on GPUs
Primary database modelSearch engineRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score6.34
Rank#55  Overall
#6  Search engines
Score1.85
Rank#118  Overall
#57  Relational DBMS
Websiteazure.microsoft.com/­en-us/­services/­searchwww.omnisci.com
Technical documentationdocs.microsoft.com/­en-us/­azure/­searchdocs.omnisci.com/­latest
DeveloperMicrosoftMapD Technologies, Inc.
Initial release20152016
Current releaseV1V4
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; enterprise edition available
Cloud-based only infoOnly available as a cloud serviceyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ and CUDA
Server operating systemshostedLinux
Data schemeyesyes
Typing infopredefined data types such as float or dateyesyes
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.nono
Secondary indexesyesno
SQL infoSupport of SQLnoyes
APIs and other access methodsRESTful HTTP APIJDBC
ODBC
Thrift
Supported programming languages.Net
C#
All languages supporting JDBC/ODBC/Thrift
Python
Server-side scripts infoStored proceduresnono
Triggersnono
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding infoRound robin
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceMaster-master replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanono
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
User concepts infoAccess controlyes infousing Azure authenticationfine grained access rights according to SQL-standard

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More resources
Microsoft Azure SearchOmniSci infoFormerly named 'MapD', rebranded to 'OmniSci' in September 2018
DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

show all

Recent citations in the news

Cognitive Search - Azure Search with AI | Azure Friday - Microsoft
6 September 2019, Channel 9

Knowledge Mining with Azure Search | AI Show - Microsoft
8 October 2019, Channel 9

Knowledge mining using the knowledge store feature of Azure Search - Microsoft
17 September 2019, Channel 9

Azure Cognitive Search brings knowledge mining to the enterprise
21 November 2019, SDTimes.com

How to use Azure Search in .Net
23 April 2018, InfoWorld

provided by Google News

GPU Database Market to Witness Huge Growth by 2027 | Kinetica DB , Neo4j, OmniSci, SQream Technologies
27 March 2020, Skyline Gazette

GPU Database Market Report by Geographical Segmentation 2020 Kinetica, Omnisci, Sqream
2 March 2020, NJ MMA News

OmniSci 'Hitting Its Stride,' CEO Says
25 October 2019, Datanami

Inside OmniSci's Plans for Data Analytics Convergence
23 October 2019, Datanami

Review: OmniSci GPU database lifts huge data sets
1 April 2019, InfoWorld

provided by Google News

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