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DBMS > HEAVY.AI vs. Microsoft Azure AI Search vs. PouchDB vs. Sphinx

System Properties Comparison HEAVY.AI vs. Microsoft Azure AI Search vs. PouchDB vs. Sphinx

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Editorial information provided by DB-Engines
NameHEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonPouchDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionA high performance, column-oriented RDBMS, specifically developed to harness the massive parallelism of modern CPU and GPU hardwareSearch-as-a-service for web and mobile app developmentJavaScript DBMS with an API inspired by CouchDBOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSSearch engineDocument storeSearch engine
Secondary database modelsSpatial DBMSVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.41
Rank#153  Overall
#71  Relational DBMS
Score5.75
Rank#58  Overall
#7  Search engines
Score2.18
Rank#114  Overall
#21  Document stores
Score5.97
Rank#56  Overall
#5  Search engines
Websitegithub.com/­heavyai/­heavydb
www.heavy.ai
azure.microsoft.com/­en-us/­services/­searchpouchdb.comsphinxsearch.com
Technical documentationdocs.heavy.ailearn.microsoft.com/­en-us/­azure/­searchpouchdb.com/­guidessphinxsearch.com/­docs
DeveloperHEAVY.AI, Inc.MicrosoftApache Software FoundationSphinx Technologies Inc.
Initial release2016201520122001
Current release5.10, January 2022V17.1.1, June 20193.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache Version 2; enterprise edition availablecommercialOpen SourceOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++ and CUDAJavaScriptC++
Server operating systemsLinuxhostedserver-less, requires a JavaScript environment (browser, Node.js)FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesschema-freeyes
Typing infopredefined data types such as float or dateyesyesnono
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.nonono
Secondary indexesnoyesyes infovia viewsyes infofull-text index on all search fields
SQL infoSupport of SQLyesnonoSQL-like query language (SphinxQL)
APIs and other access methodsJDBC
ODBC
Thrift
Vega
RESTful HTTP APIHTTP REST infoonly for PouchDB Server
JavaScript API
Proprietary protocol
Supported programming languagesAll languages supporting JDBC/ODBC/Thrift
Python
C#
Java
JavaScript
Python
JavaScriptC++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnonoView functions in JavaScriptno
Triggersnonoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infoRound robinSharding infoImplicit feature of the cloud serviceSharding infowith a proxy-based framework, named couchdb-loungeSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationyes infoImplicit feature of the cloud serviceMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Foreign keys infoReferential integritynononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backendyes 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.yesnoyes
User concepts infoAccess controlfine grained access rights according to SQL-standardyes infousing Azure authenticationnono

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More resources
HEAVY.AI infoFormerly named 'OmniSci', rebranded to 'HEAVY.AI' in March 2022Microsoft Azure AI SearchPouchDBSphinx
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Recent citations in the news

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15 August 2024, Center for Data Innovation

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11 September 2024, insideBIGDATA

Dr. Mike Flaxman, VP or Product Management at HEAVY.AI – Interview Series
19 September 2024, Unite.AI

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19 April 2023, Business Wire

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