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DBMS > Google Cloud Firestore vs. MongoDB vs. Spark SQL

System Properties Comparison Google Cloud Firestore vs. MongoDB vs. Spark SQL

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Editorial information provided by DB-Engines
NameGoogle Cloud Firestore  Xexclude from comparisonMongoDB  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionCloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructureSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeDocument storeRelational DBMS
Secondary database modelsSpatial DBMS
Search engine infointegrated Lucene index, currently in MongoDB Atlas only.
Time Series DBMS infoTime Series Collections introduced in Release 5.0
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score9.32
Rank#52  Overall
#10  Document stores
Score478.24
Rank#5  Overall
#1  Document stores
Score22.86
Rank#35  Overall
#21  Relational DBMS
Websitefirebase.google.com/­products/­firestorewww.mongodb.comspark.apache.org/­sql
Technical documentationfirebase.google.com/­docs/­firestoredocs.mongodb.com/­manualspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperGoogleMongoDB, IncApache Software Foundation
Initial release201720092014
Current release5.0.8, April 20223.2.0, October 2021
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 2.0
Cloud-based only infoOnly available as a cloud serviceyesno infoMongoDB available as DBaaS (MongoDB Atlas)no
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.
  • MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.
Implementation languageC++Scala
Server operating systemshostedLinux
OS X
Solaris
Windows
Linux
OS X
Windows
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
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, decimal, boolean, date, object_id, geospatialyes
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 SQLnoRead-only SQL queries via the MongoDB Connector for BISQL-like DML and DDL statements
APIs and other access methodsAndroid
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API
proprietary protocol using JSONJDBC
ODBC
Supported programming languagesGo
Java
JavaScript
JavaScript (Node.js)
Objective-C
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
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
Java
Python
R
Scala
Server-side scripts infoStored proceduresyes, Firebase Rules & Cloud FunctionsJavaScriptno
Triggersyes, with Cloud Functionsyes infoin MongoDB Atlas onlyno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoPartitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.yes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-source replicationMulti-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication
none
MapReduce infoOffers an API for user-defined Map/Reduce methodsUsing Cloud Dataflowyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency infocan be individually decided for each write operation
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 datayesMulti-document ACID Transactions with snapshot isolationno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infooptional, enabled by defaultyes
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 3.2no
User concepts infoAccess controlAccess rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.Access rights for users and rolesno
More information provided by the system vendor
Google Cloud FirestoreMongoDBSpark SQL
Specific characteristicsMongoDB’s application data platform provides developers a unified interface to power...
» 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 metrics200+ million downloads, over 1.5M Atlas database clusters under management handling...
» 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
Google Cloud FirestoreMongoDBSpark SQL
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