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

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

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Editorial information provided by DB-Engines
NameGridGain  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionGridGain is an in-memory computing platform, built on Apache IgniteSearch-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 modelKey-value store
Relational DBMS
Search engineSearch engine
Secondary database modelsVector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.47
Rank#154  Overall
#26  Key-value stores
#72  Relational DBMS
Score5.59
Rank#63  Overall
#7  Search engines
Score5.98
Rank#56  Overall
#5  Search engines
Websitewww.gridgain.comazure.microsoft.com/­en-us/­services/­searchsphinxsearch.com
Technical documentationwww.gridgain.com/­docs/­index.htmllearn.microsoft.com/­en-us/­azure/­searchsphinxsearch.com/­docs
DeveloperGridGain Systems, Inc.MicrosoftSphinx Technologies Inc.
Initial release200720152001
Current releaseGridGain 8.5.1V13.5.1, February 2023
License infoCommercial or Open SourcecommercialcommercialOpen 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 languageJava, C++, .NetC++
Server operating systemsLinux
OS X
Solaris
Windows
hostedFreeBSD
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.yesno
Secondary indexesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLANSI-99 for query and DML statements, subset of DDLnoSQL-like query language (SphinxQL)
APIs and other access methodsHDFS API
Hibernate
JCache
JDBC
ODBC
Proprietary protocol
RESTful HTTP API
Spring Data
RESTful HTTP APIProprietary protocol
Supported programming languagesC#
C++
Java
PHP
Python
Ruby
Scala
C#
Java
JavaScript
Python
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyes (compute grid and cache interceptors can be used instead)nono
Triggersyes (cache interceptors and events)nono
Partitioning methods infoMethods for storing different data on different nodesShardingSharding 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 nodesyes (replicated cache)yes infoImplicit feature of the cloud servicenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes (compute grid and hadoop accelerator)nono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynonono
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 persistentyesyesyes 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.yesno
User concepts infoAccess controlSecurity Hooks for custom implementationsyes infousing Azure authenticationno

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More resources
GridGainMicrosoft Azure AI SearchSphinx
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