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DBMS > Amazon Aurora vs. Apache Spark (SQL) vs. Microsoft Azure Data Explorer

System Properties Comparison Amazon Aurora vs. Apache Spark (SQL) vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines
NameAmazon Aurora  Xexclude from comparisonApache Spark (SQL)  Xexclude from comparisonMicrosoft Azure Data Explorer  Xexclude from comparison
DescriptionMySQL and PostgreSQL compatible cloud service by AmazonApache Spark SQL is a component on top of 'Spark Core' for structured data processingFully managed big data interactive analytics platform
Primary database modelRelational DBMSRelational DBMSRelational DBMS infocolumn oriented
Secondary database modelsDocument storeDocument 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
DB-Engines Ranking infomeasures the popularity of database management systemsranking trend
Trend Chart
Score7.48
Rank#45  Overall
#28  Relational DBMS
Score17.39
Rank#32  Overall
#20  Relational DBMS
Score3.09
Rank#83  Overall
#46  Relational DBMS
Websiteaws.amazon.com/­rds/­auroraspark.apache.org/­sqlazure.microsoft.com/­services/­data-explorer
Technical documentationdocs.aws.amazon.com/­AmazonRDS/­latest/­AuroraUserGuide/­CHAP_Aurora.htmlspark.apache.org/­docs/­latest/­sql-programming-guide.htmldocs.microsoft.com/­en-us/­azure/­data-explorer
DeveloperAmazonApache Software FoundationMicrosoft
Initial release201520142019
Current release3.5.0 ( 2.13), September 2023cloud service with continuous releases
License infoCommercial or Open SourcecommercialOpen Source infoApache 2.0commercial
Cloud-based only infoOnly available as a cloud serviceyesnoyes
DBaaS offerings (sponsored links) infoDatabase as a Service

Providers of DBaaS offerings, please contact us to be listed.
Implementation languageScala
Server operating systemshostedLinux
OS X
Windows
hosted
Data schemeyesyesFixed schema with schema-less datatypes (dynamic)
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-types
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.yesnoyes
Secondary indexesyesnoall fields are automatically indexed
SQL infoSupport of SQLyesSQL-like DML and DDL statementsKusto Query Language (KQL), SQL subset
APIs and other access methodsADO.NET
JDBC
ODBC
JDBC
ODBC
Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP 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
Java
Python
R
Scala
.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R
Server-side scripts infoStored proceduresyesnoYes, possible languages: KQL, Python, R
Triggersyesnoyes infosee docs.microsoft.com/­en-us/­azure/­kusto/­management/­updatepolicy
Partitioning methods infoMethods for storing different data on different nodeshorizontal partitioningyes, utilizing Spark CoreSharding infoImplicit feature of the cloud service
Replication methods infoMethods for redundantly storing data on multiple nodesSource-replica replicationnoneyes infoImplicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.
MapReduce infoOffers an API for user-defined Map/Reduce methodsnoSpark connector (open source): github.com/­Azure/­azure-kusto-spark
Consistency concepts infoMethods to ensure consistency in a distributed systemImmediate ConsistencyEventual Consistency
Immediate Consistency
Foreign keys infoReferential integrityyesnono
Transaction concepts infoSupport to ensure data integrity after non-atomic manipulations of dataACIDnono
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.yesnono
User concepts infoAccess controlfine grained access rights according to SQL-standardnoAzure Active Directory Authentication

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More resources
Amazon AuroraApache Spark (SQL)Microsoft Azure Data Explorer
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