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DBMS > Amazon DocumentDB vs. FoundationDB vs. Google Cloud Datastore vs. TDSQL for MySQL

System Properties Comparison Amazon DocumentDB vs. FoundationDB vs. Google Cloud Datastore vs. TDSQL for MySQL

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonFoundationDB  Xexclude from comparisonGoogle Cloud Datastore  Xexclude from comparisonTDSQL for MySQL  Xexclude from comparison
Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market. As a consequence, the product was removed from the DB-Engines ranking. In April 2018, Apple open-sourced FoundationDB and it therefore reappears in the ranking.
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceOrdered key-value store. Core features are complimented by layers.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud PlatformA high-performance distributed database management system with features such as automatic sharding, intelligent operation and maintenance, elastic scalability without downtime, and enterprise-grade security. It is highly compatible with MySQL.
Primary database modelDocument storeDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Document storeRelational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.91
Rank#132  Overall
#24  Document stores
Score1.03
Rank#190  Overall
#31  Document stores
#28  Key-value stores
#89  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Score0.85
Rank#205  Overall
#95  Relational DBMS
Websiteaws.amazon.com/­documentdbgithub.com/­apple/­foundationdbcloud.google.com/­datastorewww.tencentcloud.com/­products/­dcdb
Technical documentationaws.amazon.com/­documentdb/­resourcesapple.github.io/­foundationdbcloud.google.com/­datastore/­docswww.tencentcloud.com/­document/­product/­1042
DeveloperFoundationDBGoogleTencent
Initial release2019201320082013
Current release6.2.28, November 2020
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialcommercial
Cloud-based only infoOnly available as a cloud serviceyesnoyesyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageC++
Server operating systemshostedLinux
OS X
Windows
hostedhosted
Data schemeschema-freeschema-free infosome layers support schemasschema-freeyes
Typing infopredefined data types such as float or dateyesno infosome layers support typingyes, 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
Secondary indexesyesnoyesyes
SQL infoSupport of SQLnosupported in specific SQL layer onlySQL-like query language (GQL)yes
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)gRPC (using protocol buffers) API
RESTful HTTP/JSON API
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
C
C#
C++
Java
PHP
Python
Ruby
Server-side scripts infoStored proceduresnoin SQL-layer onlyusing Google App Engineyes
TriggersnonoCallbacks using the Google Apps Engineyes
Partitioning methods infoMethods for storing different data on different nodesnoneShardingShardingAutomatic sharding
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesMulti-source replication using PaxosMulti-source replication
Source-replica replication
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)noyes infousing Google Cloud Dataflowno
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyLinearizable consistencyImmediate 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 possiblein SQL-layer onlyyes infovia ReferenceProperties or Ancestor pathsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACID infoSerializable Isolation within Transactions, Read Committed outside of TransactionsACID
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
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.nono
User concepts infoAccess controlAccess rights for users and rolesnoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)Users with fine-grained authorization concept

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More resources
Amazon DocumentDBFoundationDBGoogle Cloud DatastoreTDSQL for MySQL
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