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DBMS > Amazon DocumentDB vs. FatDB vs. Google Cloud Datastore vs. H2GIS vs. InterSystems IRIS

System Properties Comparison Amazon DocumentDB vs. FatDB vs. Google Cloud Datastore vs. H2GIS vs. InterSystems IRIS

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonH2GIS  Xexclude from comparisonInterSystems IRIS  Xexclude from comparison
FatDB/FatCloud has ceased operations as a company with February 2014. FatDB is discontinued and excluded from the ranking.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceA .NET NoSQL DBMS that can integrate with and extend SQL Server.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformSpatial extension of H2A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalability
Primary database modelDocument storeDocument store
Key-value store
Document storeSpatial DBMSDocument store
Key-value store
Object oriented DBMS
Relational DBMS
Secondary database modelsRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score4.47
Rank#76  Overall
#12  Document stores
Score0.00
Rank#383  Overall
#7  Spatial DBMS
Score4.05
Rank#83  Overall
#14  Document stores
#10  Key-value stores
#1  Object oriented DBMS
#45  Relational DBMS
Websiteaws.amazon.com/­documentdbcloud.google.com/­datastorewww.h2gis.orgwww.intersystems.com/­products/­intersystems-iris
Technical documentationaws.amazon.com/­documentdb/­resourcescloud.google.com/­datastore/­docswww.h2gis.org/­docs/­homedocs.intersystems.com/­irislatest/­csp/­docbook/­DocBook.UI.Page.cls
DeveloperFatCloudGoogleCNRSInterSystems
Initial release20192012200820132018
Current release2023.3, June 2023
License infoCommercial or Open SourcecommercialcommercialcommercialOpen Source infoLGPL 3.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#Java
Server operating systemshostedWindowshostedAIX
Linux
macOS
Ubuntu
Windows
Data schemeschema-freeschema-freeschema-freeyesdepending on used data model
Typing infopredefined data types such as float or dateyesyesyes, details hereyesyes
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.nononoyes
Secondary indexesyesyesyesyesyes
SQL infoSupport of SQLnono infoVia inetgration in SQL ServerSQL-like query language (GQL)yesyes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible).NET Client API
LINQ
RESTful HTTP API
RPC
Windows WCF Bindings
gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
RESTful HTTP API
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Java.Net
C++
Java
JavaScript (Node.js)
Python
Server-side scripts infoStored proceduresnoyes infovia applicationsusing Google App Engineyes infobased on H2yes
Triggersnoyes infovia applicationsCallbacks using the Google Apps Engineyesyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingnoneSharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasselectable replication factorMulti-source replication using Paxosyes infobased on H2Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesyes infousing Google Cloud Dataflownono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Immediate Consistency or Eventual Consistency depending on type of query and configuration infoStrong Consistency is default for entity lookups and queries within an Entity Group (but can instead be made eventually consistent). Other queries are always eventual consistent.Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyes infovia ReferenceProperties or Ancestor pathsyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACIDACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes, multi-version concurrency control (MVCC)yes
Durability infoSupport for making data persistentyesyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyesyes
User concepts infoAccess controlAccess rights for users and rolesno infoCan implement custom security layer via applicationsAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)yes infobased on H2yes
More information provided by the system vendor
Amazon DocumentDBFatDBGoogle Cloud DatastoreH2GISInterSystems IRIS
Specific characteristicsInterSystems IRIS is a complete cloud-first data platform which includes a multi-model...
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More resources
Amazon DocumentDBFatDBGoogle Cloud DatastoreH2GISInterSystems IRIS
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