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DBMS > Hive vs. MongoDB vs. Prometheus

System Properties Comparison Hive vs. MongoDB vs. Prometheus

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Editorial information provided by DB-Engines
NameHive  Xexclude from comparisonMongoDB  Xexclude from comparisonPrometheus  Xexclude from comparison
Descriptiondata warehouse software for querying and managing large distributed datasets, built on HadoopOne of the most popular document stores available both as a fully managed cloud service and for deployment on self-managed infrastructureOpen-source TimeSeries DBMS and monitoring system
Primary database modelRelational DBMSDocument storeTime Series DBMS
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
Score81.61
Rank#17  Overall
#11  Relational DBMS
Score478.24
Rank#5  Overall
#1  Document stores
Score6.13
Rank#67  Overall
#3  Time Series DBMS
Websitehive.apache.orgwww.mongodb.comprometheus.io
Technical documentationcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.mongodb.com/­manualprometheus.io/­docs
DeveloperApache Software Foundation infoinitially developed by FacebookMongoDB, Inc
Initial release201220092015
Current release3.1.2, August 20195.0.8, April 2022
License infoCommercial or Open SourceOpen Source infoApache Version 2Open 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 infoApache 2.0
Cloud-based only infoOnly available as a cloud servicenono infoMongoDB available as DBaaS (MongoDB Atlas)no
DBaaS offerings (sponsored links) infoDatabase as a Service

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  • MongoDB Atlas: Global multi-cloud database with unmatched data distribution and mobility across AWS, Azure, and Google Cloud, built-in automation for resource and workload optimization, and so much more.
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Implementation languageJavaC++Go
Server operating systemsAll OS with a Java VMLinux
OS X
Solaris
Windows
Linux
Windows
Data schemeyesschema-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, geospatialNumeric data only
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 infoImport of XML data possible
Secondary indexesyesyesno
SQL infoSupport of SQLSQL-like DML and DDL statementsRead-only SQL queries via the MongoDB Connector for BIno
APIs and other access methodsJDBC
ODBC
Thrift
proprietary protocol using JSONRESTful HTTP/JSON API
Supported programming languagesC++
Java
PHP
Python
Actionscript 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
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
.Net
C++
Go
Haskell
Java
JavaScript (Node.js)
Python
Ruby
Server-side scripts infoStored proceduresyes infouser defined functions and integration of map-reduceJavaScriptno
Triggersnoyes infoin MongoDB Atlas onlyno
Partitioning methods infoMethods for storing different data on different nodesShardingSharding infoPartitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.Sharding
Replication methods infoMethods for redundantly storing data on multiple nodesselectable replication factorMulti-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication
yes infoby Federation
MapReduce infoOffers an API for user-defined Map/Reduce methodsyes infoquery execution via MapReduceyesno
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency infocan be individually decided for each write operation
none
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 datanoMulti-document ACID Transactions with snapshot isolationno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyes infooptional, enabled by defaultyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yes infoIn-memory storage engine introduced with MongoDB version 3.2no
User concepts infoAccess controlAccess rights for users, groups and rolesAccess rights for users and rolesno
More information provided by the system vendor
HiveMongoDBPrometheus
Specific characteristicsMongoDB’s application data platform provides developers a unified interface to power...
» 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 metrics200+ million downloads, over 1.5M Atlas database clusters under management handling...
» more
Licensing and pricing modelsMongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

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