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DBMS > Google Search Appliance vs. Hypertable vs. MongoDB

System Properties Comparison Google Search Appliance vs. Hypertable vs. MongoDB

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Editorial information provided by DB-Engines
NameGoogle Search Appliance  Xexclude from comparisonHypertable  Xexclude from comparisonMongoDB  Xexclude from comparison
Hypertable has stopped its further development with March 2016 and is removed from the DB-Engines ranking.
DescriptionThe Google Search Appliance consists of hardware and software for indexing documents in local networks.An open source BigTable implementation based on distributed file systems such as HadoopOne of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructure
Primary database modelSearch engineWide column 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
Score2.86
Rank#86  Overall
#9  Search engines
Score412.09
Rank#5  Overall
#1  Document stores
Websiteenterprise.google.com/­search/­products/­gsa.htmlwww.mongodb.com
Technical documentationsupport.google.com/­gsadocs.mongodb.com/­manual
DeveloperGoogleHypertable Inc.MongoDB, Inc
Initial release200220092009
Current release0.9.8.11, March 20164.2, August 2019
License infoCommercial or Open SourcecommercialOpen Source infoGNU version 3. Commercial license availableOpen 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 servicenonono infoMongoDB available as DBaaS (MongoDB Atlas)
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++
Server operating systemsLinux
OS X
Windows infoan inofficial Windows port is available
Linux
OS X
Solaris
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.
Typing infopredefined data types such as float or datenoyes 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 indexesrestricted infoonly exact value or prefix value scansyes
SQL infoSupport of SQLnonoRead-only SQL queries via the MongoDB Connector for BI
APIs and other access methodsAdministrative API
Browser interface
HTTP API
C++ API
Thrift
proprietary protocol using JSON
Supported programming languagesC++
Java
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
Scala
Smalltalk infoinofficial driver
Server-side scripts infoStored proceduresnoJavaScript
Triggersnoyes infoin MongoDB Atlas only
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding infopartitioned by hashed, ranged, or zoned sharding keys
Replication methods infoMethods for redundantly storing data on multiple nodesMaster-slave replicationselectable replication factor on file system levelMaster-slave replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesyes
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 datanoMulti-document ACID Transactions with snapshot isolation
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes 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 controlUser authentication via various security protocolsnoAccess rights for users and roles
More information provided by the system vendor
Google Search ApplianceHypertableMongoDB
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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We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources
Google Search ApplianceHypertableMongoDB
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