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DBMS > Lovefield vs. Microsoft Azure AI Search vs. Sphinx

System Properties Comparison Lovefield vs. Microsoft Azure AI Search vs. Sphinx

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Editorial information provided by DB-Engines
NameLovefield  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionEmbeddable relational database for web apps written in pure JavaScriptSearch-as-a-service for web and mobile app developmentOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelRelational DBMSSearch engineSearch engine
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.32
Rank#290  Overall
#132  Relational DBMS
Score5.71
Rank#64  Overall
#8  Search engines
Score6.03
Rank#60  Overall
#6  Search engines
Websitegoogle.github.io/­lovefieldazure.microsoft.com/­en-us/­services/­searchsphinxsearch.com
Technical documentationgithub.com/­google/­lovefield/­blob/­master/­docs/­spec_index.mdlearn.microsoft.com/­en-us/­azure/­searchsphinxsearch.com/­docs
DeveloperGoogleMicrosoftSphinx Technologies Inc.
Initial release201420152001
Current release2.1.12, February 2017V13.5.1, February 2023
License infoCommercial or Open SourceOpen Source infoApache 2.0commercialOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud servicenoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaScriptC++
Server operating systemsserver-less, requires a JavaScript environment (browser, Node.js) infotested with Chrome, Firefox, IE, SafarihostedFreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeyesyesyes
Typing infopredefined data types such as float or dateyesyesno
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 indexesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query language infovia JavaScript builder patternnoSQL-like query language (SphinxQL)
APIs and other access methodsRESTful HTTP APIProprietary protocol
Supported programming languagesJavaScriptC#
Java
JavaScript
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnonono
TriggersUsing read-only observersnono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud serviceSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesnoneyes infoImplicit feature of the cloud servicenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes, by using IndexedDB or the cloud service Firebase Realtime Databaseyesyes 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 infousing MemoryDBno
User concepts infoAccess controlnoyes infousing Azure authenticationno

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More resources
LovefieldMicrosoft Azure AI SearchSphinx
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