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DBMS > Amazon DocumentDB vs. FoundationDB vs. Microsoft Azure SQL Database vs. Postgres-XL vs. Spark SQL

System Properties Comparison Amazon DocumentDB vs. FoundationDB vs. Microsoft Azure SQL Database vs. Postgres-XL vs. Spark SQL

Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonFoundationDB  Xexclude from comparisonMicrosoft Azure SQL Database infoformerly SQL Azure  Xexclude from comparisonPostgres-XL  Xexclude from comparisonSpark SQL  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Created as commercial project in 2013, FoundationDB has been acquired by Apple in March 2015 and was withdrawn from the market.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.Database as a Service offering with high compatibility to Microsoft SQL ServerBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeDocument store infosupported via specific layer
Key-value store
Relational DBMS infosupported via specific SQL-layer
Relational DBMSRelational DBMSRelational DBMS
Secondary database modelsDocument store
Graph DBMS
Spatial DBMS
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
Score1.03
Rank#190  Overall
#31  Document stores
#28  Key-value stores
#89  Relational DBMS
Score77.99
Rank#16  Overall
#11  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score18.96
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­documentdbgithub.com/­apple/­foundationdbazure.microsoft.com/­en-us/­products/­azure-sql/­databasewww.postgres-xl.orgspark.apache.org/­sql
Technical documentationaws.amazon.com/­documentdb/­resourcesapple.github.io/­foundationdbdocs.microsoft.com/­en-us/­azure/­azure-sqlwww.postgres-xl.org/­documentationspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperFoundationDBMicrosoftApache Software Foundation
Initial release2019201320102014 infosince 2012, originally named StormDB2014
Current release6.2.28, November 2020V1210 R1, October 20183.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercialOpen Source infoMozilla public licenseOpen Source infoApache 2.0
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++C++CScala
Server operating systemshostedLinux
OS X
Windows
hostedLinux
macOS
Linux
OS X
Windows
Data schemeschema-freeschema-free infosome layers support schemasyesyesyes
Typing infopredefined data types such as float or dateyesno infosome layers support typingyesyesyes
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.noyesyes infoXML type, but no XML query functionalityno
Secondary indexesyesnoyesyesno
SQL infoSupport of SQLnosupported in specific SQL layer onlyyesyes infodistributed, parallel query executionSQL-like DML and DDL statements
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)ADO.NET
JDBC
ODBC
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
.Net
C
C++
Go
Java
JavaScript infoNode.js
PHP
Python
Ruby
Swift
.Net
C#
Java
JavaScript (Node.js)
PHP
Python
Ruby
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoin SQL-layer onlyTransact SQLuser defined functionsno
Triggersnonoyesyesno
Partitioning methods infoMethods for storing different data on different nodesnoneShardinghorizontal partitioningyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesMulti-availability zones for high availability, asynchronous replication for up to 15 read replicasyesyes, with always 3 replicas availablenone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)nonono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyLinearizable consistencyImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possiblein SQL-layer onlyyesyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDACIDACID infoMVCCno
Concurrency infoSupport for concurrent manipulation of datayesyesyesyesyes
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.nono
User concepts infoAccess controlAccess rights for users and rolesnofine grained access rights according to SQL-standardfine grained access rights according to SQL-standardno

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More resources
Amazon DocumentDBFoundationDBMicrosoft Azure SQL Database infoformerly SQL AzurePostgres-XLSpark SQL
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