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DBMS > Memcached vs. Microsoft Azure AI Search vs. MongoDB

System Properties Comparison Memcached vs. Microsoft Azure AI Search vs. MongoDB

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Editorial information provided by DB-Engines
NameMemcached  Xexclude from comparisonMicrosoft Azure AI Search  Xexclude from comparisonMongoDB  Xexclude from comparison
DescriptionIn-memory key-value store, originally intended for cachingSearch-as-a-service for web and mobile app developmentOne of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelKey-value storeSearch engineDocument store
Secondary database modelsVector DBMSSpatial DBMS
Search engine infointegrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS infoTime Series Collections introduced in Release 5.0
Vector DBMS infocurrently available in the MongoDB Atlas cloud service only
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score15.47
Rank#34  Overall
#4  Key-value stores
Score5.28
Rank#61  Overall
#7  Search engines
Score402.51
Rank#5  Overall
#1  Document stores
Websitewww.memcached.orgazure.microsoft.com/­en-us/­services/­searchwww.mongodb.com
Technical documentationgithub.com/­memcached/­memcached/­wikilearn.microsoft.com/­en-us/­azure/­searchwww.mongodb.com/­docs/­manual
DeveloperDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalMicrosoftMongoDB, Inc
Initial release200320152009
Current release1.6.29, June 2024V17.0.5, January 2024
License infoCommercial or Open SourceOpen Source infoBSD licensecommercialOpen Source infoMongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.
Cloud-based only infoOnly available as a cloud servicenoyesno infoMongoDB available as DBaaS (MongoDB Atlas)
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCC++
Server operating systemsFreeBSD
Linux
OS X
Unix
Windows
hostedLinux
OS X
Solaris
Windows
Data schemeschema-freeyesschema-free infoAlthough schema-free, documents of the same collection often follow the same structure. Optionally impose all or part of a schema by defining a JSON schema.
Typing infopredefined data types such as float or datenoyesyes infostring, integer, double, decimal, boolean, date, object_id, geospatial
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.no
Secondary indexesnoyesyes
SQL infoSupport of SQLnonoRead-only SQL queries via the MongoDB Atlas SQL Interface
APIs and other access methodsProprietary protocolRESTful HTTP APIGraphQL
HTTP REST
Prisma
proprietary protocol using JSON
Supported programming languages.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
C#
Java
JavaScript
Python
Actionscript infounofficial driver
C
C#
C++
Clojure infounofficial driver
ColdFusion infounofficial driver
D infounofficial driver
Dart infounofficial driver
Delphi infounofficial driver
Erlang
Go
Groovy infounofficial driver
Haskell
Java
JavaScript
Kotlin
Lisp infounofficial driver
Lua infounofficial driver
MatLab infounofficial driver
Perl
PHP
PowerShell infounofficial driver
Prolog infounofficial driver
Python
R infounofficial driver
Ruby
Rust
Scala
Smalltalk infounofficial driver
Swift
Server-side scripts infoStored proceduresnonoJavaScript
Triggersnonoyes infoin MongoDB Atlas only
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoImplicit feature of the cloud serviceSharding infoPartitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoRepcached, a Memcached patch, provides this functionallityyes infoImplicit feature of the cloud serviceMulti-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infocan be individually decided for each read operation
Immediate Consistency infodefault behaviour
Foreign keys infoReferential integritynonono infotypically not used, however similar functionality with DBRef possible
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanonoMulti-document ACID Transactions with snapshot isolation
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentnoyesyes infooptional, enabled by default
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes infoIn-memory storage engine introduced with MongoDB version 3.2
User concepts infoAccess controlyes infousing SASL (Simple Authentication and Security Layer) protocolyes infousing Azure authenticationAccess rights for users and roles
More information provided by the system vendor
MemcachedMicrosoft Azure AI SearchMongoDB
Specific characteristicsMongoDB provides an integrated suite of cloud database and data services to accelerate...
» more
Competitive advantagesBuilt around the flexible document data model and unified API, MongoDB is a developer...
» more
Typical application scenariosAI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
» more
Key customersADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more
Market metricsHundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
» more
Licensing and pricing modelsMongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

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MemcachedMicrosoft Azure AI SearchMongoDB
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