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DBMS > Apache Phoenix vs. Microsoft Azure Table Storage vs. MongoDB

System Properties Comparison Apache Phoenix vs. Microsoft Azure Table Storage vs. MongoDB

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Editorial information provided by DB-Engines
NameApache Phoenix  Xexclude from comparisonMicrosoft Azure Table Storage  Xexclude from comparisonMongoDB  Xexclude from comparison
DescriptionA scale-out RDBMS with evolutionary schema built on Apache HBaseA 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 infrastructure
Primary database modelRelational DBMSWide column storeDocument store
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
Score3.39
Rank#94  Overall
#47  Relational DBMS
Score5.28
Rank#70  Overall
#5  Wide column stores
Score457.22
Rank#5  Overall
#1  Document stores
Websitephoenix.apache.orgazure.microsoft.com/­en-us/­services/­storage/­tableswww.mongodb.com
Technical documentationphoenix.apache.orgdocs.mongodb.com/­manual
DeveloperApache Software FoundationMicrosoftMongoDB, Inc
Initial release201420122009
Current release5.0-HBase2, July 2018 and 4.15-HBase1, December 20194.4.3 , December 2020
License infoCommercial or Open SourceOpen Source infoApache Version 2.0commercialOpen 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

Providers of DBaaS offerings, please contact us to be listed.
  • ScaleGrid for MongoDB: Fully managed hosting for MongoDB database on AWS, Azure and DigitalOcean with high availability and SSH access on the #1 multi-cloud DBaaS.
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Implementation languageJavaC++
Server operating systemsLinux
Unix
Windows
hostedLinux
OS X
Solaris
Windows
Data schemeyes infolate-bound, schema-on-read capabilitiesschema-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.
Typing infopredefined data types such as float or dateyesyesyes 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.nono
Secondary indexesyesnoyes
SQL infoSupport of SQLyesnoRead-only SQL queries via the MongoDB Connector for BI
APIs and other access methodsJDBCRESTful HTTP APIproprietary protocol using JSON
Supported programming languagesC
C#
C++
Groovy
Java
PHP
Python
Scala
.Net
C#
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby
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
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 proceduresuser defined functionsnoJavaScript
Triggersnonoyes infoin MongoDB Atlas only
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoImplicit feature of the cloud serviceSharding infopartitioned by hashed, ranged, or zoned sharding keys
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replication
Source-replica replication
yes 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
MapReduce infoOffers an API for user-defined Map/Reduce methodsHadoop integrationnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency infocan be individually decided for each write operation
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 dataACIDoptimistic lockingMulti-document ACID Transactions with snapshot isolation
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infooptional
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesnoyes infoIn-memory storage engine introduced with MongoDB version 3.2
User concepts infoAccess controlAccess Control Lists (using HBase ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC, multi-tenancyAccess rights based on private key authentication or shared access signaturesAccess rights for users and roles
More information provided by the system vendor
Apache PhoenixMicrosoft Azure Table StorageMongoDB
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
Apache PhoenixMicrosoft Azure Table StorageMongoDB
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