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DBMS > Google BigQuery vs. JSqlDb vs. MongoDB

System Properties Comparison Google BigQuery vs. JSqlDb vs. MongoDB

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonJSqlDb  Xexclude from comparisonMongoDB  Xexclude from comparison
JSqlDB seems to be discontinued. Therefore it is excluded from the DB-Engines ranking.
DescriptionLarge scale data warehouse service with append-only tablesJavaScript Query Language Database, stores JavaScript objects and primitivesOne of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelRelational DBMSDocument store
Object oriented DBMS
Document store
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
Score54.64
Rank#20  Overall
#14  Relational DBMS
Score425.36
Rank#5  Overall
#1  Document stores
Websitecloud.google.com/­bigqueryjsqldb.org (offline)www.mongodb.com
Technical documentationcloud.google.com/­bigquery/­docsdocs.mongodb.com/­manual
DeveloperGoogleKonrad von BackstromMongoDB, Inc
Initial release201020182009
Current release0.8, December 20186.0.5, March 2023
License infoCommercial or Open SourcecommercialOpen SourceOpen 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 serviceyesnono infoMongoDB available as DBaaS (MongoDB Atlas)
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++
Server operating systemshostedLinux
macOS
Windows
Linux
OS X
Solaris
Windows
Data schemeyesschema-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 dateyesnoyes 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 indexesnonoyes
SQL infoSupport of SQLyesnoRead-only SQL queries via the MongoDB Atlas SQL Interface
APIs and other access methodsRESTful HTTP/JSON APIGraphQL
HTTP REST
Prisma
proprietary protocol using JSON
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
JavaScriptActionscript 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
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptfunctions in JavaScriptJavaScript
Triggersnonoyes infoin MongoDB Atlas only
Partitioning methods infoMethods for storing different data on different nodesnonenoneSharding infoPartitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesnoneMulti-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnonoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency infocan be individually decided for each read operation
Immediate Consistency infodefault behaviour
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 datano infoSince BigQuery is designed for querying dataMulti-document ACID Transactions with snapshot isolation
Concurrency infoSupport for concurrent manipulation of datayesyes
Durability infoSupport for making data persistentyesyes infousing RocksDByes infooptional, enabled by default
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 3.2
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 roles
More information provided by the system vendor
Google BigQueryJSqlDbMongoDB
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 scenariosInternet of Things and Time Series (Bosch, GE Healthcare, Jaguar Land Rover) Mobile...
» more
Key customersADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more
Market metrics365+ million downloads, over 150,000+ Atlas clusters provisioned every month handling...
» 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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More resources
Google BigQueryJSqlDbMongoDB
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