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DBMS > Google BigQuery vs. MongoDB vs. MySQL

System Properties Comparison Google BigQuery vs. MongoDB vs. MySQL

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonMongoDB  Xexclude from comparisonMySQL  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesOne of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructureWidely used open source RDBMS
Primary database modelRelational DBMSDocument storeRelational DBMS infoKey/Value like access via memcached API
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
Vector DBMS infocurrently available in the MongoDB Atlas cloud service only
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score61.90
Rank#19  Overall
#13  Relational DBMS
Score423.96
Rank#5  Overall
#1  Document stores
Score1087.72
Rank#2  Overall
#2  Relational DBMS
Websitecloud.google.com/­bigquerywww.mongodb.comwww.mysql.com
Technical documentationcloud.google.com/­bigquery/­docswww.mongodb.com/­docs/­manualdev.mysql.com/­doc
DeveloperGoogleMongoDB, IncOracle infosince 2010, originally MySQL AB, then Sun
Initial release201020091995
Current release6.0.7, June 20238.3.0, January 2024
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 infoGPL version 2. Commercial licenses with extended functionallity are available
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.
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.Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.
Implementation languageC++C and C++
Server operating systemshostedLinux
OS X
Solaris
Windows
FreeBSD
Linux
OS X
Solaris
Windows
Data schemeyesschema-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.noyes
Secondary indexesnoyesyes
SQL infoSupport of SQLyesRead-only SQL queries via the MongoDB Atlas SQL Interfaceyes infowith proprietary extensions
APIs and other access methodsRESTful HTTP/JSON APIGraphQL
HTTP REST
Prisma
proprietary protocol using JSON
ADO.NET
JDBC
ODBC
Proprietary native API
Supported programming languages.Net
Java
JavaScript
Objective-C
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
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
Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptJavaScriptyes infoproprietary syntax
Triggersnoyes infoin MongoDB Atlas onlyyes
Partitioning methods infoMethods for storing different data on different nodesnoneSharding infoPartitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication
Multi-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infocan be individually decided for each read operation
Immediate Consistency infodefault behaviour
Immediate Consistency
Foreign keys infoReferential integritynono infotypically not used, however similar functionality with DBRef possibleyes infonot for MyISAM storage engine
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datano infoSince BigQuery is designed for querying dataMulti-document ACID Transactions with snapshot isolationACID infonot for MyISAM storage engine
Concurrency infoSupport for concurrent manipulation of datayesyesyes infotable locks or row locks depending on storage engine
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.noyes infoIn-memory storage engine introduced with MongoDB version 3.2yes
User concepts infoAccess controlAccess privileges (owner, writer, reader) on dataset, table or view level infoGoogle Cloud Identity & Access Management (IAM)Access rights for users and rolesUsers with fine-grained authorization concept infono user groups or roles
More information provided by the system vendor
Google BigQueryMongoDBMySQL
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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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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3rd partiesCData: Connect to Big Data & NoSQL through standard Drivers.
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Navicat for MongoDB gives you a highly effective GUI interface for MongoDB database management, administration and development.
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Navicat Monitor is a safe, simple and agentless remote server monitoring tool for MySQL and many other database management systems.
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Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.
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Navicat for MySQL is the ideal solution for MySQL/MariaDB administration and development.
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CData: Connect to Big Data & NoSQL through standard Drivers.
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We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Google BigQueryMongoDBMySQL
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