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DBMS > Amazon DocumentDB vs. GigaSpaces vs. MonetDB vs. PouchDB

System Properties Comparison Amazon DocumentDB vs. GigaSpaces vs. MonetDB vs. PouchDB

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonGigaSpaces  Xexclude from comparisonMonetDB  Xexclude from comparisonPouchDB  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceHigh performance in-memory data grid platform, powering three products: Smart Cache, Smart ODS (Operational Data Store), Smart Augmented TransactionsA relational database management system that stores data in columnsJavaScript DBMS with an API inspired by CouchDB
Primary database modelDocument storeDocument store
Object oriented DBMS infoValues are user defined objects
Relational DBMSDocument store
Secondary database modelsGraph DBMS
Search engine
Document store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score0.97
Rank#192  Overall
#32  Document stores
#6  Object oriented DBMS
Score1.72
Rank#145  Overall
#67  Relational DBMS
Score2.28
Rank#115  Overall
#21  Document stores
Websiteaws.amazon.com/­documentdbwww.gigaspaces.comwww.monetdb.orgpouchdb.com
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.gigaspaces.com/­latest/­landing.htmlwww.monetdb.org/­Documentationpouchdb.com/­guides
DeveloperGigaspaces TechnologiesMonetDB BVApache Software Foundation
Initial release2019200020042012
Current release15.5, September 2020Dec2023 (11.49), December 20237.1.1, June 2019
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2; Commercial licenses availableOpen Source infoMozilla Public License 2.0Open Source
Cloud-based only infoOnly available as a cloud serviceyesnonono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJava, C++, .NetCJavaScript
Server operating systemshostedLinux
macOS
Solaris
Windows
FreeBSD
Linux
OS X
Solaris
Windows
server-less, requires a JavaScript environment (browser, Node.js)
Data schemeschema-freeschema-freeyesschema-free
Typing infopredefined data types such as float or dateyesyesyesno
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.nono infoXML can be used for describing objects metadatano
Secondary indexesyesyesyesyes infovia views
SQL infoSupport of SQLnoSQL-99 for query and DML statementsyes infoSQL 2003 with some extensionsno
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)GigaSpaces LRMI
Hibernate
JCache
JDBC
JPA
ODBC
RESTful HTTP API
Spring Data
JDBC
native C library infoMAPI library (MonetDB application programming interface)
ODBC
HTTP REST infoonly for PouchDB Server
JavaScript API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
C++
Java
Python
Scala
C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
JavaScript
Server-side scripts infoStored proceduresnoyesyes, in SQL, C, RView functions in JavaScript
Triggersnoyes, event driven architectureyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingSharding via remote tablesSharding infowith a proxy-based framework, named couchdb-lounge
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasMulti-source replication infosynchronous or asynchronous
Source-replica replication infosynchronous or asynchronous
none infoSource-replica replication available in experimental statusMulti-source replication infoalso with CouchDB databases
Source-replica replication infoalso with CouchDB databases
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yes infoMap-Reduce pattern can be built with XAP task executorsnoyes
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency infoConsistency level configurable: ALL, QUORUM, ANYEventual Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyesyes infoby using IndexedDB, WebSQL or LevelDB as backend
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes
User concepts infoAccess controlAccess rights for users and rolesRole-based access controlfine grained access rights according to SQL-standardno

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More resources
Amazon DocumentDBGigaSpacesMonetDBPouchDB
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