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DBMS > Amazon CloudSearch vs. Hive vs. Microsoft Azure Data Explorer vs. Postgres-XL vs. PostgreSQL

System Properties Comparison Amazon CloudSearch vs. Hive vs. Microsoft Azure Data Explorer vs. Postgres-XL vs. PostgreSQL

Editorial information provided by DB-Engines
NameAmazon CloudSearch  Xexclude from comparisonHive  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparisonPostgres-XL  Xexclude from comparisonPostgreSQL  Xexclude from comparison
DescriptionA hosted search engine service by Amazon with the data stored in Amazons clouddata warehouse software for querying and managing large distributed datasets, built on HadoopFully managed big data interactive analytics platformBased on PostgreSQL enhanced with MPP and write-scale-out cluster featuresWidely used open source RDBMS infoDeveloped as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL
Primary database modelSearch engineRelational DBMSRelational DBMS infocolumn orientedRelational DBMSRelational DBMS infowith object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.
Secondary database modelsDocument store infoIf a column is of type dynamic docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-types/­dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store infothis is the general usage pattern at Microsoft. Billing, Logs, Telemetry events are stored in ADX and the state of an individual entity is defined by the arg_max(timestamps)
Spatial DBMS
Search engine infosupport for complex search expressions docs.microsoft.com/­en-us/­azure/­kusto/­query/­parseoperator FTS, Geospatial docs.microsoft.com/­en-us/­azure/­kusto/­query/­geo-point-to-geohash-function distributed search -> ADX acts as a distributed search engine
Time Series DBMS infosee docs.microsoft.com/­en-us/­azure/­data-explorer/­time-series-analysis
Document store
Spatial DBMS
Document store
Graph DBMS infowith Apache Age
Spatial DBMS
Vector DBMS infowith pgvector extension
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score1.85
Rank#137  Overall
#12  Search engines
Score61.17
Rank#18  Overall
#12  Relational DBMS
Score4.38
Rank#77  Overall
#41  Relational DBMS
Score0.49
Rank#256  Overall
#117  Relational DBMS
Score645.54
Rank#4  Overall
#4  Relational DBMS
Websiteaws.amazon.com/­cloudsearchhive.apache.orgazure.microsoft.com/­services/­data-explorerwww.postgres-xl.orgwww.postgresql.org
Technical documentationdocs.aws.amazon.com/­cloudsearchcwiki.apache.org/­confluence/­display/­Hive/­Homedocs.microsoft.com/­en-us/­azure/­data-explorerwww.postgres-xl.org/­documentationwww.postgresql.org/­docs
DeveloperAmazonApache Software Foundation infoinitially developed by FacebookMicrosoftPostgreSQL Global Development Group infowww.postgresql.org/­developer
Initial release2012201220192014 infosince 2012, originally named StormDB1989 info1989: Postgres, 1996: PostgreSQL
Current release3.1.3, April 2022cloud service with continuous releases10 R1, October 201816.3, May 2024
License infoCommercial or Open SourcecommercialOpen Source infoApache Version 2commercialOpen Source infoMozilla public licenseOpen Source infoBSD
Cloud-based only infoOnly available as a cloud serviceyesnoyesnono
DBaaS offerings (sponsored links) infoDatabase as a Service

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Implementation languageJavaCC
Server operating systemshostedAll OS with a Java VMhostedLinux
macOS
FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)yesyes
Typing infopredefined data types such as float or dateyesyesyes infobool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/­en-us/­azure/­kusto/­query/­scalar-data-typesyesyes
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.yesyes infoXML type, but no XML query functionalityyes infospecific XML-type available, but no XML query functionality.
Secondary indexesyes infoall search fields are automatically indexedyesall fields are automatically indexedyesyes
SQL infoSupport of SQLnoSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subsetyes infodistributed, parallel query executionyes infostandard with numerous extensions
APIs and other access methodsHTTP APIJDBC
ODBC
Thrift
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
ADO.NET
JDBC
native C library
ODBC
streaming API for large objects
Supported programming languagesC++
Java
PHP
Python
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl
.Net
C
C++
Delphi
Java infoJDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl
Server-side scripts infoStored proceduresnoyes infouser defined functions and integration of map-reduceYes, possible languages: KQL, Python, Ruser defined functionsuser defined functions inforealized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.
Triggersnonoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicyyesyes
Partitioning methods infoMethods for storing different data on different nodesyes infoautomatic partitioning across Amazon Search Instance as requiredShardingSharding infoImplicit feature of the cloud servicehorizontal partitioningpartitioning by range, list and (since PostgreSQL 11) by hash
Replication methods infoMethods for redundantly storing data on multiple nodesyes infomanaged transparently by AWSselectable replication factoryes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.Source-replica replication infoother methods possible by using 3rd party extensions
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoyes infoquery execution via MapReduceSpark connector (open source): github.com/­Azure/­azure-kusto-sparknono
Consistency concepts infoMethods to ensure consistency in a distributed systemEventual ConsistencyEventual Consistency
Immediate Consistency
Immediate ConsistencyImmediate Consistency
Foreign keys infoReferential integritynononoyesyes
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of datanononoACID infoMVCCACID
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.nonono
User concepts infoAccess controlauthentication via encrypted signaturesAccess rights for users, groups and rolesAzure Active Directory Authenticationfine grained access rights according to SQL-standardfine grained access rights according to SQL-standard

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More resources
Amazon CloudSearchHiveMicrosoft Azure Data ExplorerPostgres-XLPostgreSQL
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