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DBMS > Hazelcast vs. MongoDB vs. Sphinx

System Properties Comparison Hazelcast vs. MongoDB vs. Sphinx

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Editorial information provided by DB-Engines
NameHazelcast  Xexclude from comparisonMongoDB  Xexclude from comparisonSphinx  Xexclude from comparison
DescriptionA widely adopted in-memory data gridOne of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructureOpen source search engine for searching in data from different sources, e.g. relational databases
Primary database modelKey-value storeDocument storeSearch engine
Secondary database modelsDocument store infoJSON support with IMDG 3.12Search engine infointegrated Lucene index, currently in MongoDB Atlas only.
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.71
Rank#45  Overall
#5  Key-value stores
Score412.09
Rank#5  Overall
#1  Document stores
Score7.39
Rank#47  Overall
#5  Search engines
Websitehazelcast.comwww.mongodb.comsphinxsearch.com
Technical documentationhazelcast.org/­documentationdocs.mongodb.com/­manualsphinxsearch.com/­docs
DeveloperHazelcastMongoDB, IncSphinx Technologies Inc.
Initial release200820092001
Current release3.12.2, August 20194.2, August 20193.1.1, October 2018
License infoCommercial or Open SourceOpen Source infoApache Version 2; commercial licenses availableOpen 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 licence 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 languageJavaC++C++
Server operating systemsAll OS with a Java VMLinux
OS X
Solaris
Windows
FreeBSD
Linux
NetBSD
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.yes
Typing infopredefined data types such as float or dateyesyes infostring, integer, double, decimal, boolean, date, object_id, geospatialno
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.yes infothe object must implement a serialization strategy
Secondary indexesyesyesyes infofull-text index on all search fields
SQL infoSupport of SQLSQL-like query languageRead-only SQL queries via the MongoDB Connector for BISQL-like query language (SphinxQL)
APIs and other access methodsJCache
JPA
Memcached protocol
RESTful HTTP API
proprietary protocol using JSONProprietary protocol
Supported programming languages.Net
C#
C++
Clojure
Go
Java
JavaScript (Node.js)
Python
Scala
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
C++ infounofficial client library
Java
Perl infounofficial client library
PHP
Python
Ruby infounofficial client library
Server-side scripts infoStored proceduresyes infoEvent Listeners, Executor ServicesJavaScriptno
Triggersyes infoEventsyes infoin MongoDB Atlas onlyno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infopartitioned by hashed, ranged, or zoned sharding keysSharding infoPartitioning is done manually, search queries against distributed index is supported
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoReplicated MapMaster-slave replicationnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate Consistency or Eventual Consistency selectable by user infoRaft Consensus AlgorithmEventual Consistency
Immediate Consistency infocan be individually decided for each write operation
Foreign keys infoReferential integritynono infotypically not used, however similar functionality with DBRef possibleno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataone or two-phase-commit; repeatable reads; read commitedMulti-document ACID Transactions with snapshot isolationno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infooptionalyes infoThe original contents of fields are not stored in the Sphinx index.
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes infoIn-memory storage engine introduced with MongoDB version 3.2
User concepts infoAccess controlRole-based access controlAccess rights for users and rolesno
More information provided by the system vendor
HazelcastMongoDBSphinx
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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More resources
HazelcastMongoDBSphinx
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