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DBMS > Greenplum vs. Hypertable vs. MongoDB

System Properties Comparison Greenplum vs. Hypertable vs. MongoDB

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Editorial information provided by DB-Engines
NameGreenplum  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.
DescriptionAnalytic Database platform built on PostgreSQL. Full name is Pivotal Greenplum Database infoA logical database in Greenplum is an array of individual PostgreSQL databases working together to present a single database image.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 modelRelational DBMSWide column storeDocument store
Secondary database modelsDocument store
Spatial DBMS
Spatial 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
Score13.47
Rank#42  Overall
#26  Relational DBMS
Score496.16
Rank#5  Overall
#1  Document stores
Websitegreenplum.orgwww.mongodb.com
Technical documentationdocs.greenplum.orgdocs.mongodb.com/­manual
DeveloperPivotal Software Inc.Hypertable Inc.MongoDB, Inc
Initial release200520092009
Current release6.7.1, April 20200.9.8.11, March 20165.0, July 2021
License infoCommercial or Open SourceOpen Source infoApache 2.0Open 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.
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Implementation languageC++C++
Server operating systemsLinuxLinux
OS X
Windows infoan inofficial Windows port is available
Linux
OS X
Solaris
Windows
Data schemeyesschema-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 dateyesnoyes 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.yes infosince Version 4.2
Secondary indexesyesrestricted infoonly exact value or prefix value scansyes
SQL infoSupport of SQLyesnoRead-only SQL queries via the MongoDB Connector for BI
APIs and other access methodsJDBC
ODBC
C++ API
Thrift
proprietary protocol using JSON
Supported programming languagesC
Java
Perl
Python
R
C++
Java
Perl
PHP
Python
Ruby
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
Server-side scripts infoStored proceduresyesnoJavaScript
Triggersyesnoyes infoin MongoDB Atlas only
Partitioning methods infoMethods for storing different data on different nodesShardingShardingSharding 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 nodesSource-replica replicationselectable replication factor on file system levelMulti-Source deployments with MongoDB Atlas Global Clusters
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsyesyesyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate ConsistencyEventual Consistency
Immediate Consistency infocan be individually decided for each write operation
Foreign keys infoReferential integrityyesnono infotypically not used, however similar functionality with DBRef possible
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnoMulti-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.noyes infoIn-memory storage engine introduced with MongoDB version 3.2
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAccess rights for users and roles
More information provided by the system vendor
GreenplumHypertableMongoDB
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 metrics175 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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More resources
GreenplumHypertableMongoDB
DB-Engines blog posts

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Conferences and events

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