DBMS > Amazon Aurora vs. Microsoft Azure Data Explorer

System Properties Comparison Amazon Aurora vs. Microsoft Azure Data Explorer

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Our visitors often compare Amazon Aurora and Microsoft Azure Data Explorer with OpenSearch, Microsoft Azure Cosmos DB and TimescaleDB.

Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

Fully managed big data interactive analytics platform

Primary database model

Relational DBMS

column oriented

Secondary database models

Document store

If 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

this 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

support 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

see docs.microsoft.com/en-us/azure/data-explorer/time-series-analysis

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	7.48
Rank	#45	Overall
	#28	Relational DBMS

Score	3.09
Rank	#83	Overall
	#46	Relational DBMS

Website

aws.amazon.com/rds/aurora

azure.microsoft.com/services/data-explorer

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

docs.microsoft.com/en-us/azure/data-explorer

Developer

Amazon

Microsoft

Initial release

2015

2019

Current release

cloud service with continuous releases

License

Commercial or Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Server operating systems

hosted

Data scheme

yes

Fixed schema with schema-less datatypes (dynamic)

Typing

predefined data types such as float or date

yes

bool, datetime, dynamic, guid, int, long, real, string, timespan, double: docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types

XML support

Some form of processing data in XML format, e.g. support for XML data structures, and/or support for XPath, XQuery or XSLT.

yes

Secondary indexes

yes

all fields are automatically indexed

SQL

Support of SQL

yes

Kusto Query Language (KQL), SQL subset

APIs and other access methods

ADO.NET
JDBC
ODBC

Microsoft SQL Server communication protocol (MS-TDS)
RESTful HTTP API

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
Go
Java
JavaScript (Node.js)
PowerShell
Python
R

Server-side scripts

Stored procedures

yes

Yes, possible languages: KQL, Python, R

Triggers

yes

see docs.microsoft.com/en-us/azure/kusto/management/updatepolicy

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

Implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

MapReduce

Offers an API for user-defined Map/Reduce methods

Spark connector (open source): github.com/Azure/azure-kusto-spark

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

fine grained access rights according to SQL-standard

Azure Active Directory Authentication

More information provided by the system vendor

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

Related products and services

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

Amazon - the rising star in the DBMS market
3 August 2015, Matthias Gelbmann

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Recent citations in the news

Introducing Amazon Aurora DSQL | Amazon Web Services
3 December 2024, AWS Blog

Accelerate your generative AI application development with Amazon Bedrock Knowledge Bases Quick Create and Amazon Aurora Serverless
7 December 2024, AWS Blog

AWS introduces Amazon Aurora DSQL and DynamoDB enhancements for multi-region workloads
3 December 2024, SiliconANGLE News

New Amazon CloudWatch Database Insights: Comprehensive database observability from fleets to instances
1 December 2024, AWS Blog

Introducing scaling to 0 capacity with Amazon Aurora Serverless v2
20 November 2024, AWS Blog

provided by Google News

Azure Data Explorer: Log and telemetry analytics benchmark
16 August 2022, Microsoft

Microsoft is closing down another Azure-based feature in the near future
22 July 2024, Neowin

Microsoft announces general availability of Azure Data Explorer and Azure Data Lake Storage Gen2
7 February 2019, VentureBeat

Log and Telemetry Analytics Performance Benchmark
16 August 2022, Gigaom

Azure Data Explorer Technology 101
18 July 2023, Microsoft

provided by Google News

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