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DBMS > Microsoft Azure Table Storage vs. MongoDB vs. Solr

System Properties Comparison Microsoft Azure Table Storage vs. MongoDB vs. Solr

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Editorial information provided by DB-Engines
NameMicrosoft Azure Table Storage  Xexclude from comparisonMongoDB  Xexclude from comparisonSolr  Xexclude from comparison
DescriptionA Wide Column Store for rapid development using massive semi-structured datasetsOne of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructureA widely used distributed, scalable search engine based on Apache Lucene
Primary database modelWide column storeDocument storeSearch engine
Secondary database modelsSearch engine infointegrated Lucene index, currently in MongoDB Atlas only.
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score5.77
Rank#66  Overall
#5  Wide column stores
Score446.48
Rank#5  Overall
#1  Document stores
Score51.62
Rank#20  Overall
#3  Search engines
Websiteazure.microsoft.com/­en-us/­services/­storage/­tableswww.mongodb.comlucene.apache.org/­solr
Technical documentationdocs.mongodb.com/­manuallucene.apache.org/­solr/­resources.html
DeveloperMicrosoftMongoDB, IncApache Software Foundation
Initial release201220092006
Current release4.4.1, September 20208.6.2, September 2020
License infoCommercial or Open SourcecommercialOpen Source infoMongoDB Inc.'s Server Side Public License v1. Prior versions were published under GNU AGPL v3.0. Commercial licenses are also available.Open Source infoApache Version 2
Cloud-based only infoOnly available as a cloud serviceyesno infoMongoDB available as DBaaS (MongoDB Atlas)no
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Java
Server operating systemshostedLinux
OS X
Solaris
Windows
All OS with a Java VM inforuns as a servlet in servlet container (e.g. Tomcat, Jetty is included)
Data schemeschema-freeschema-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.yes infoDynamic Fields enables on-the-fly addition of new fields
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, decimal, boolean, date, object_id, geospatialyes infosupports customizable data types and automatic typing
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
Secondary indexesnoyesyes infoAll search fields are automatically indexed
SQL infoSupport of SQLnoRead-only SQL queries via the MongoDB Connector for BISolr Parallel SQL Interface
APIs and other access methodsRESTful HTTP APIproprietary protocol using JSONJava API
RESTful HTTP/JSON API
Supported programming languages.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
Actionscript infoinofficial driver
C
C#
C++
Clojure infoinofficial driver
ColdFusion infoinofficial driver
D infoinofficial driver
Dart infoinofficial driver
Delphi infoinofficial driver
Erlang
Go
Groovy infoinofficial driver
Haskell
Java
JavaScript
Lisp infoinofficial driver
Lua infoinofficial driver
MatLab infoinofficial driver
Perl
PHP
PowerShell infoinofficial driver
Prolog infoinofficial driver
Python
R infoinofficial driver
Ruby
Rust
Scala
Smalltalk infoinofficial driver
Swift
.Net
Erlang
Java
JavaScript
any language that supports sockets and either XML or JSON
Perl
PHP
Python
Ruby
Scala
Server-side scripts infoStored proceduresnoJavaScriptJava plugins
Triggersnoyes infoin MongoDB Atlas onlyyes infoUser configurable commands triggered on index changes
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud serviceSharding infopartitioned by hashed, ranged, or zoned sharding keysSharding
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoimplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Multi-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication
yes
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesspark-solr: github.com/­lucidworks/­spark-solr and streaming expressions to reduce
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency infocan be individually decided for each write operation
Eventual Consistency
Foreign keys infoReferential integritynono infotypically not used, however similar functionality with DBRef possibleno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataoptimistic lockingMulti-document ACID Transactions with snapshot isolationoptimistic locking
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infooptionalyes
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 3.2yes
User concepts infoAccess controlAccess rights based on private key authentication or shared access signaturesAccess rights for users and rolesyes
More information provided by the system vendor
Microsoft Azure Table StorageMongoDBSolr
Specific characteristicsMongoDB is the leading modern, general purpose data platform, designed to unleash...
» more
Competitive advantagesThe MongoDB platform can be used by developers building transactional, operational,...
» more
Typical application scenariosInternet of Things and Time Series (Bosch, Jaguar Land Rover) Mobile (The Weather...
» more
Key customersADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more
Market metrics125 million downloads (growing at more than 30 thousand downloads per day), over...
» more
Licensing and pricing modelsMongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

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More resources
Microsoft Azure Table StorageMongoDBSolr
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