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DBMS > Amazon DocumentDB vs. Microsoft Azure Synapse Analytics vs. Spark SQL

System Properties Comparison Amazon DocumentDB vs. Microsoft Azure Synapse Analytics vs. Spark SQL

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Editorial information provided by DB-Engines
NameAmazon DocumentDB  Xexclude from comparisonMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data Warehouse  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionFast, scalable, highly available, and fully managed MongoDB-compatible database serviceElastic, large scale data warehouse service leveraging the broad eco-system of SQL ServerSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelDocument storeRelational DBMSRelational DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.89
Rank#137  Overall
#24  Document stores
Score22.71
Rank#30  Overall
#18  Relational DBMS
Score19.15
Rank#33  Overall
#20  Relational DBMS
Websiteaws.amazon.com/­documentdbazure.microsoft.com/­services/­synapse-analyticsspark.apache.org/­sql
Technical documentationaws.amazon.com/­documentdb/­resourcesdocs.microsoft.com/­azure/­synapse-analyticsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMicrosoftApache Software Foundation
Initial release201920162014
Current release3.5.0 ( 2.13), September 2023
License infoCommercial or Open SourcecommercialcommercialOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesyesno
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageC++Scala
Server operating systemshostedhostedLinux
OS X
Windows
Data schemeschema-freeyesyes
Typing infopredefined data types such as float or dateyesyesyes
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 indexesyesyesno
SQL infoSupport of SQLnoyesSQL-like DML and DDL statements
APIs and other access methodsproprietary protocol using JSON (MongoDB compatible)ADO.NET
JDBC
ODBC
JDBC
ODBC
Supported programming languagesGo
Java
JavaScript (Node.js)
PHP
Python
C#
Java
PHP
Java
Python
R
Scala
Server-side scripts infoStored proceduresnoTransact SQLno
Triggersnonono
Partitioning methods infoMethods for storing different data on different nodesnoneSharding, horizontal 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 replicasyesnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsno infomay be implemented via Amazon Elastic MapReduce (Amazon EMR)no
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integrityno infotypically not used, however similar functionality with DBRef possibleno infodocs.microsoft.com/­en-us/­azure/­synapse-analytics/­sql-data-warehouse/­sql-data-warehouse-table-constraintsno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataAtomic single-document operationsACIDno
Concurrency infoSupport for concurrent manipulation of datayesyesyes
Durability infoSupport for making data persistentyesyesyes
In-memory capabilities infoIs there an option to define some or all structures to be held in-memory only.no
User concepts infoAccess controlAccess rights for users and rolesyesno

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More resources
Amazon DocumentDBMicrosoft Azure Synapse Analytics infopreviously named Azure SQL Data WarehouseSpark SQL
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