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DBMS > Google Search Appliance vs. MongoDB vs. Splice Machine

System Properties Comparison Google Search Appliance vs. MongoDB vs. Splice Machine

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Editorial information provided by DB-Engines
NameGoogle Search Appliance  Xexclude from comparisonMongoDB  Xexclude from comparisonSplice Machine  Xexclude from comparison
DescriptionThe Google Search Appliance consists of hardware and software for indexing documents in local networks.One of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructureOpen-Source SQL RDBMS powered by Spark and Hadoop
Primary database modelSearch engineDocument storeRelational DBMS
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
Score2.77
Rank#94  Overall
#10  Search engines
Score413.18
Rank#5  Overall
#1  Document stores
Score0.72
Rank#178  Overall
#89  Relational DBMS
Websiteenterprise.google.com/­search/­products/­gsa.htmlwww.mongodb.comwww.splicemachine.com
Technical documentationsupport.google.com/­gsadocs.mongodb.com/­manualdoc.splicemachine.com
DeveloperGoogleMongoDB, IncJohn Leach
Initial release200220092014
Current release4.2, August 20192.0
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 infoextended commercial Enterprise edition available
Cloud-based only infoOnly available as a cloud servicenono 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: Deploy a fully managed cloud database on-demand and ready for use in minutes. Available on AWS, Azure, and GCP.
Implementation languageC++Java
Server operating systemsLinux
OS X
Solaris
Windows
Linux
OS X
Solaris
Windows
Data schemeschema-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 dateyes 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.no
Secondary indexesyesyes
SQL infoSupport of SQLnoRead-only SQL queries via the MongoDB Connector for BIyes
APIs and other access methodsAdministrative API
Browser interface
HTTP API
proprietary protocol using JSONJDBC
ODBC
Supported programming languagesActionscript 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
Java
JRuby
Scala
Server-side scripts infoStored proceduresJavaScriptyes infoJava
Triggersyes infoin MongoDB Atlas onlyyes
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infopartitioned by hashed, ranged, or zoned sharding keysSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMaster-slave replicationMaster-slave replicationMaster-master replication
Master-slave replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyesno infouses HBase instead
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual Consistency
Immediate Consistency infocan be individually decided for each write operation
Immediate Consistency
Foreign keys infoReferential integritynono infotypically not used, however similar functionality with DBRef possibleyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataMulti-document ACID Transactions with snapshot isolationACID
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infooptionalyes
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 controlUser authentication via various security protocolsAccess rights for users and rolesAccess rights for users, groups and roles according to SQL-standard
More information provided by the system vendor
Google Search ApplianceMongoDBSplice Machine
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
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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
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