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DBMS > Amazon DocumentDB vs. FatDB vs. Google Cloud Datastore vs. Interbase

System Properties Comparison Amazon DocumentDB vs. FatDB vs. Google Cloud Datastore vs. Interbase

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonFatDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonInterbase  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 PlatformLight-weight proven RDBMS infooriginally from Borland
Primary database modelDocument storeDocument store
Key-value store
Document storeRelational 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
Score4.61
Rank#72  Overall
#39  Relational DBMS
Websiteaws.amazon.com/­documentdbcloud.google.com/­datastorewww.embarcadero.com/­products/­interbase
Technical documentationaws.amazon.com/­documentdb/­resourcescloud.google.com/­datastore/­docsdocs.embarcadero.com/­products/­interbase
DeveloperFatCloudGoogleEmbarcadero
Initial release2019201220081984
Current releaseInterBase 2020, December 2019
License infoCommercial or Open Sourcecommercialcommercialcommercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC#C
Server operating systemshostedWindowshostedAndroid
iOS
Linux
OS X
Windows
Data schemeschema-freeschema-freeschema-freeyes
Typing infopredefined data types such as float or dateyesyesyes, details hereyes
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.nonono infoexport as XML data possible
Secondary indexesyesyesyesyes
SQL infoSupport of SQLnono infoVia inetgration in SQL ServerSQL-like query language (GQL)yes
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
ADO.NET
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Delphi
Java
Object Pascal
PHP
Ruby
Server-side scripts infoStored proceduresnoyes infovia applicationsusing Google App Engineyes infoInterbase procedure and trigger language
Triggersnoyes infovia applicationsCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingnone
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 PaxosInterbase Change Views
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)yesyes infousing Google Cloud Dataflowno
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 Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblenoyes infovia ReferenceProperties or Ancestor pathsyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsnoACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes infoMultiversion concurreny control
Durability infoSupport for making data persistentyesyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.noyes
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)fine grained access rights according to SQL-standard

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More resources
Amazon DocumentDBFatDBGoogle Cloud DatastoreInterbase
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