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DBMS > Amazon Aurora vs. Datomic vs. FoundationDB vs. Google Cloud Datastore

System Properties Comparison Amazon Aurora vs. Datomic vs. FoundationDB vs. Google Cloud Datastore

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonDatomic  Xexclude from comparisonFoundationDB  Xexclude from comparisonGoogle Cloud Datastore  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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.
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonDatomic builds on immutable values, supports point-in-time queries and uses 3rd party systems for durabilityOrdered key-value store. Core features are complimented by layers.Automatically scaling NoSQL Database as a Service (DBaaS) on the Google Cloud Platform
Primary database modelRelational DBMSRelational DBMSDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Document store
Secondary database modelsDocument store
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.91
Rank#50  Overall
#32  Relational DBMS
Score1.59
Rank#150  Overall
#69  Relational DBMS
Score1.03
Rank#190  Overall
#31  Document stores
#28  Key-value stores
#89  Relational DBMS
Score4.47
Rank#76  Overall
#12  Document stores
Websiteaws.amazon.com/­rds/­aurorawww.datomic.comgithub.com/­apple/­foundationdbcloud.google.com/­datastore
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmldocs.datomic.comapple.github.io/­foundationdbcloud.google.com/­datastore/­docs
DeveloperAmazonCognitectFoundationDBGoogle
Initial release2015201220132008
Current release1.0.6735, June 20236.2.28, November 2020
License infoCommercial or Open Sourcecommercialcommercial infolimited edition freeOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnonoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageJava, ClojureC++
Server operating systemshostedAll OS with a Java VMLinux
OS X
Windows
hosted
Data schemeyesyesschema-free infosome layers support schemasschema-free
Typing infopredefined data types such as float or dateyesyesno infosome layers support typingyes, details here
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.yesnono
Secondary indexesyesyesnoyes
SQL infoSupport of SQLyesnosupported in specific SQL layer onlySQL-like query language (GQL)
APIs and other access methodsADO.NET
JDBC
ODBC
RESTful HTTP APIgRPC (using protocol buffers) API
RESTful HTTP/JSON API
Supported programming languagesAda
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl
Clojure
Java
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
.Net
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Server-side scripts infoStored proceduresyesyes infoTransaction Functionsin SQL-layer onlyusing Google App Engine
TriggersyesBy using transaction functionsnoCallbacks using the Google Apps Engine
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningnone infoBut extensive use of caching in the application peersShardingSharding
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnone infoBut extensive use of caching in the application peersyesMulti-source replication using Paxos
MapReduce infoOffers an API for user-defined Map/Reduce methodsnononoyes infousing Google Cloud Dataflow
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate 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.
Foreign keys infoReferential integrityyesnoin SQL-layer onlyyes infovia ReferenceProperties or Ancestor paths
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDACIDACIDACID infoSerializable Isolation within Transactions, Read Committed outside of Transactions
Concurrency infoSupport for concurrent manipulation of datayesyesyesyes
Durability infoSupport for making data persistentyesyes infousing external storage systems (e.g. Cassandra, DynamoDB, PostgreSQL, Couchbase and others)yesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.yesyes inforecommended only for testing and developmentno
User concepts infoAccess controlfine grained access rights according to SQL-standardnonoAccess rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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More resources
Amazon AuroraDatomicFoundationDBGoogle Cloud Datastore
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