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DBMS > Amazon DocumentDB vs. Hazelcast vs. Microsoft Azure AI Search vs. mSQL vs. Sphinx

System Properties Comparison Amazon DocumentDB vs. Hazelcast vs. Microsoft Azure AI Search vs. mSQL vs. Sphinx

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonHazelcast  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonmSQL infoMini SQL  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceA widely adopted in-memory data gridSearch-as-a-service for web and mobile app developmentmSQL (Mini SQL) is a simple and lightweight RDBMSOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelDocument storeKey-value storeSearch engineRelational DBMSSearch engine
Secondary database modelsDocument store infoJSON support with IMDG 3.12Vector DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score5.97
Rank#57  Overall
#6  Key-value stores
Score5.59
Rank#63  Overall
#7  Search engines
Score1.27
Rank#167  Overall
#77  Relational DBMS
Score5.98
Rank#56  Overall
#5  Search engines
Websiteaws.amazon.com/­documentdbhazelcast.comazure.microsoft.com/­en-us/­services/­searchhughestech.com.au/­products/­msqlsphinxsearch.com
Technical documentationaws.amazon.com/­documentdb/­resourceshazelcast.org/­imdg/­docslearn.microsoft.com/­en-us/­azure/­searchsphinxsearch.com/­docs
DeveloperHazelcastMicrosoftHughes TechnologiesSphinx Technologies Inc.
Initial release20192008201519942001
Current release5.3.6, November 2023V14.4, October 20213.5.1, February 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; commercial licenses availablecommercialcommercial infofree licenses can be providedOpen Source infoGPL version 2, commercial licence available
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJavaCC++
Server operating systemshostedAll OS with a Java VMhostedAIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows
FreeBSD
Linux
NetBSD
OS X
Solaris
Windows
Data schemeschema-freeschema-freeyesyesyes
Typing infopredefined data types such as float or dateyesyesyesyesno
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.noyes infothe object must implement a serialization strategynono
Secondary indexesyesyesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLnoSQL-like query languagenoA subset of ANSI SQL is implemented infono subqueries, aggregate functions, views, foreign keys, triggersSQL-like query language (SphinxQL)
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)JCache
JPA
Memcached protocol
RESTful HTTP API
RESTful HTTP APIJDBC
ODBC
Proprietary protocol
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
C#
Java
JavaScript
Python
C
C++
Delphi
Java
Perl
PHP
Tcl
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresnoyes infoEvent Listeners, Executor Servicesnonono
Triggersnoyes infoEventsnonono
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding infoImplicit feature of the cloud servicenoneSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyes infoReplicated Mapyes infoImplicit feature of the cloud servicenonenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesnonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmImmediate Consistencynone
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenononono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsone or two-phase-commit; repeatable reads; read commitednonono
Concurrency infoSupport for concurrent manipulation of datayesyesyesnoyes
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.yesnono
User concepts infoAccess controlAccess rights for users and rolesRole-based access controlyes infousing Azure authenticationnono

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More resources
Amazon DocumentDBHazelcastMicrosoft Azure AI SearchmSQL infoMini SQLSphinx
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