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DBMS > GeoMesa vs. Hive vs. MongoDB

System Properties Comparison GeoMesa vs. Hive vs. MongoDB

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Editorial information provided by DB-Engines
NameGeoMesa  Xexclude from comparisonHive  Xexclude from comparisonMongoDB  Xexclude from comparison
DescriptionGeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.data 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 infrastructure
Primary database modelSpatial DBMSRelational DBMSDocument store
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
Vector DBMS infocurrently available in the MongoDB Atlas cloud service only
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score0.81
Rank#214  Overall
#4  Spatial DBMS
Score62.59
Rank#18  Overall
#12  Relational DBMS
Score423.96
Rank#5  Overall
#1  Document stores
Websitewww.geomesa.orghive.apache.orgwww.mongodb.com
Technical documentationwww.geomesa.org/­documentation/­stable/­user/­index.htmlcwiki.apache.org/­confluence/­display/­Hive/­Homewww.mongodb.com/­docs/­manual
DeveloperCCRi and othersApache Software Foundation infoinitially developed by FacebookMongoDB, Inc
Initial release201420122009
Current release4.0.5, February 20243.1.3, April 20226.0.7, June 2023
License infoCommercial or Open SourceOpen Source infoApache License 2.0Open 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.
Cloud-based only infoOnly available as a cloud servicenonono infoMongoDB available as DBaaS (MongoDB Atlas)
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.
Implementation languageScalaJavaC++
Server operating systemsAll OS with a Java VMLinux
OS X
Solaris
Windows
Data schemeyesyesschema-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 dateyesyesyes 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 indexesyesyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsRead-only SQL queries via the MongoDB Atlas SQL Interface
APIs and other access methodsJDBC
ODBC
Thrift
GraphQL
HTTP REST
Prisma
proprietary protocol using JSON
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
Kotlin
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
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceJavaScript
Triggersnonoyes infoin MongoDB Atlas only
Partitioning methods infoMethods for storing different data on different nodesdepending on storage layerShardingSharding infoPartitioned by hashed, ranged, or zoned sharding keys. Live resharding allows users to change their shard keys as an online operation with zero downtime.
Replication methods infoMethods for redundantly storing data on multiple nodesdepending on storage layerselectable replication factorMulti-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyes infoquery execution via MapReduceyes
Consistency concepts infoMethods to ensure consistency in a distributed systemdepending on storage layerEventual ConsistencyEventual Consistency infocan be individually decided for each read operation
Immediate Consistency infodefault behaviour
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 datanonoMulti-document ACID Transactions with snapshot isolation
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes infooptional, enabled by default
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.depending on storage layeryes infoIn-memory storage engine introduced with MongoDB version 3.2
User concepts infoAccess controlyes infodepending on the DBMS used for storageAccess rights for users, groups and rolesAccess rights for users and roles
More information provided by the system vendor
GeoMesaHiveMongoDB
Specific characteristicsMongoDB provides an integrated suite of cloud database and data services to accelerate...
» more
Competitive advantagesBuilt around the flexible document data model and unified API, MongoDB is a developer...
» more
Typical application scenariosAI-enriched intelligent apps (Continental, Telefonica, Iron Mountain) Internet of...
» more
Key customersADP, Adobe, Amadeus, AstraZeneca, Auto Trader, Barclays, BBVA, Bosch, Cisco, CERN,...
» more
Market metricsHundreds of millions downloads, over 150,000+ Atlas clusters provisioned every month...
» more
Licensing and pricing modelsMongoDB database server: Server-Side Public License (SSPL) . Commercial licenses...
» more

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More resources
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