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DBMS > Google BigQuery vs. Memcached vs. MongoDB

System Properties Comparison Google BigQuery vs. Memcached vs. MongoDB

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Editorial information provided by DB-Engines
NameGoogle BigQuery  Xexclude from comparisonMemcached  Xexclude from comparisonMongoDB  Xexclude from comparison
DescriptionLarge scale data warehouse service with append-only tablesIn-memory key-value store, originally intended for cachingOne of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelRelational DBMSKey-value 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
Score35.76
Rank#24  Overall
#15  Relational DBMS
Score25.89
Rank#28  Overall
#4  Key-value stores
Score457.73
Rank#5  Overall
#1  Document stores
Websitecloud.google.com/­bigquerywww.memcached.orgwww.mongodb.com
Technical documentationcloud.google.com/­bigquery/­docsgithub.com/­memcached/­memcached/­wikidocs.mongodb.com/­manual
DeveloperGoogleDanga Interactive infooriginally developed by Brad Fitzpatrick for LiveJournalMongoDB, Inc
Initial release201020032009
Current release1.6.8, October 20204.4.2, November 2020
License infoCommercial or Open SourcecommercialOpen Source infoBSD licenseOpen 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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  • 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: the global and fully-managed cloud database service from the makers of MongoDB. Deploy across AWS, Azure, or GCP.
Implementation languageCC++
Server operating systemshostedFreeBSD
Linux
OS X
Unix
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.no
Secondary indexesnonoyes
SQL infoSupport of SQLyesnoRead-only SQL queries via the MongoDB Connector for BI
APIs and other access methodsRESTful HTTP/JSON APIProprietary protocolproprietary protocol using JSON
Supported programming languages.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby
.Net
C
C++
ColdFusion
Erlang
Java
Lisp
Lua
OCaml
Perl
PHP
Python
Ruby
Actionscript 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
Rust
Scala
Smalltalk infoinofficial driver
Swift
Server-side scripts infoStored proceduresuser defined functions infoin JavaScriptnoJavaScript
Triggersnonoyes infoin MongoDB Atlas only
Partitioning methods infoMethods for storing different data on different nodesnonenoneSharding infopartitioned by hashed, ranged, or zoned sharding keys
Replication methods infoMethods for redundantly storing data on multiple nodesnone infoRepcached, a Memcached patch, provides this functionallityMulti-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
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 datano infoSince BigQuery is designed for querying datanoMulti-document ACID Transactions with snapshot isolation
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesnoyes infooptional
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) for whole datasets, not for individual tables infoGoogle Cloud Identity & Access Management (IAM)yes infousing SASL (Simple Authentication and Security Layer) protocolAccess rights for users and roles
More information provided by the system vendor
Google BigQueryMemcachedMongoDB
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

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 BigQueryMemcachedMongoDB
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