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DBMS > Microsoft Azure Search vs. PostgreSQL vs. Spark SQL

System Properties Comparison Microsoft Azure Search vs. PostgreSQL vs. Spark SQL

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Editorial information provided by DB-Engines
NameMicrosoft Azure Search  Xexclude from comparisonPostgreSQL  Xexclude from comparisonSpark SQL  Xexclude from comparison
DescriptionSearch-as-a-service for web and mobile app developmentWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQLSpark SQL is a component on top of 'Spark Core' for structured data processing
Primary database modelSearch engineRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.Relational DBMS
Secondary database modelsDocument store
Spatial DBMS
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score6.90
Rank#60  Overall
#7  Search engines
Score613.83
Rank#4  Overall
#4  Relational DBMS
Score20.15
Rank#36  Overall
#22  Relational DBMS
Websiteazure.microsoft.com/­en-us/­services/­searchwww.postgresql.orgspark.apache.org/­sql
Technical documentationdocs.microsoft.com/­en-us/­azure/­searchwww.postgresql.org/­docsspark.apache.org/­docs/­latest/­sql-programming-guide.html
DeveloperMicrosoftPostgreSQL Global Development Group infowww.postgresql.org/­developerApache Software Foundation
Initial release20151989 info1989: Postgres, 1996: PostgreSQL2014
Current releaseV115.2, February 20233.3.0 ( 2.13), June 2022
License infoCommercial or Open SourcecommercialOpen Source infoBSDOpen Source infoApache 2.0
Cloud-based only infoOnly available as a cloud serviceyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageCScala
Server operating systemshostedFreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Linux
OS X
Windows
Data schemeyesyesyes
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.noyes infospecific XML-type available, but no XML query functionality.no
Secondary indexesyesyesno
SQL infoSupport of SQLnoyes infostandard with numerous extensionsSQL-like DML and DDL statements
APIs and other access methodsRESTful HTTP APIADO.NET
JDBC
native C library
ODBC
streaming API for large objects
JDBC
ODBC
Supported programming languages.Net
C#
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Java
Python
R
Scala
Server-side scripts infoStored proceduresnouser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.no
Triggersnoyesno
Partitioning methods infoMethods for storing different data on different nodesSharding infoImplicit feature of the cloud servicepartitioning by range, list and (since PostgreSQL 11) by hashyes, utilizing Spark Core
Replication methods infoMethods for redundantly storing data on multiple nodesyes infoImplicit feature of the cloud serviceSource-replica replication infoother methods possible by using 3rd party extensionsnone
MapReduce infoOffers an API for user-defined Map/Reduce methodsnono
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynoyesno
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanoACIDno
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.nonono
User concepts infoAccess controlyes infousing Azure authenticationfine grained access rights according to SQL-standardno

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More resources
Microsoft Azure SearchPostgreSQLSpark SQL
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PGCon 2023, PostgreSQL Conference for Users and Developers
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