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DBMS > MongoDB vs. Percona Server for MongoDB vs. Spark SQL

System Properties Comparison MongoDB vs. Percona Server for MongoDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameMongoDB  Xexclude from comparisonPercona Server for MongoDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionOne of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructureA drop-in replacement for MongoDB Community Edition with enterprise-grade features.Spark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeDocument storeRelational DBMS
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
Score443.48
Rank#5  Overall
#1  Document stores
Score0.62
Rank#203  Overall
#30  Document stores
Score18.40
Rank#34  Overall
#21  Relational DBMS
Websitewww.mongodb.comwww.percona.com/­software/­mongo-database/­percona-server-for-mongodbspark.apache.org/­sql
Technical documentationdocs.mongodb.com/­manualwww.percona.com/­doc/­percona-server-for-mongodb/­LATEST/­index.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMongoDB, IncPerconaApache Software Foundation
Initial release200920152014
Current release4.2.8, June 20203.4.10-2.10, November 20173.0.0, June 2020
License infoCommercial or Open SourceOpen 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 infoGPL Version 2Open Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceno infoMongoDB available as DBaaS (MongoDB Atlas)nono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
MongoDB Atlas: Deploy a fully managed cloud database on-demand and ready for use in minutes. Available on AWS, Azure, and GCP.
Implementation languageC++C++Scala
Server operating systemsLinux
OS X
Solaris
Windows
LinuxLinux
OS X
Windows
Data schemeschema-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.schema-freeyes
Typing infopredefined data types such as float or dateyes infostring, integer, double, decimal, boolean, date, object_id, geospatialyesyes
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 indexesyesyesno
SQL infoSupport of SQLRead-only SQL queries via the MongoDB Connector for BInoSQL-like DML and DDL statements
APIs and other access methodsproprietary protocol using JSONproprietary protocol using JSONJDBC
ODBC
Supported programming languagesActionscript 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
Scala
Smalltalk infoinofficial driver
Actionscript
C
C#
C++
Clojure
ColdFusion
D
Dart
Delphi
Erlang
Go
Groovy
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Perl
PHP
PowerShell
Prolog
Python
R
Ruby
Scala
Smalltalk
Java
Python
R
Scala
Server-side scripts infoStored proceduresJavaScriptJavaScriptno
Triggersyes infoin MongoDB Atlas onlynono
Partitioning methods infoMethods for storing different data on different nodesSharding infopartitioned by hashed, ranged, or zoned sharding keysShardingyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMaster-slave replicationMaster-slave replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be individually decided for each write operation
Eventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataMulti-document ACID Transactions with snapshot isolationnono
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyes infooptionalyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoIn-memory storage engine introduced with MongoDB version 3.2yes infovia In-Memory Engineno
User concepts infoAccess controlAccess rights for users and rolesAccess rights for users and rolesno
More information provided by the system vendor
MongoDBPercona Server for MongoDBSpark SQL
Specific characteristicsMongoDB is the leading modern, general purpose data platform, designed to unleash...
» more
Competitive advantagesThe MongoDB Data Platform can be used by developers building OLTP and analytical...
» 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 metrics70 million downloads (growing at more than 30 thousand downloads per day). 15,000+...
» more
Licensing and pricing modelsMongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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More resources
MongoDBPercona Server for MongoDBSpark SQL
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