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

Document store
Spatial DBMS

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

Score	7.57
Rank	#51	Overall
	#32	Relational DBMS

Score	4.83
Rank	#67	Overall
	#4	Time Series DBMS

Score	0.17
Rank	#337	Overall
	#30	Time Series DBMS

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Website

aws.amazon.com/rds/aurora

github.com/graphite-project/graphite-web

machbase.com

azure.microsoft.com/services/data-explorer

www.mysql.com

Technical documentation

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

graphite.readthedocs.io

machbase.com/dbms

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

dev.mysql.com/doc

Developer

Amazon

Chris Davis

Machbase

Microsoft

Oracle

since 2010, originally MySQL AB, then Sun

Initial release

2015

2006

2013

2019

1995

Current release

V8.0, August 2023

cloud service with continuous releases

8.4.0, April 2024

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

commercial

free test version available

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

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.

Aiven for MySQL: Fully managed MySQL, deployable in the cloud of your choice, with seamless integrations and lightning-fast setup.

Implementation language

Python

C and C++

Server operating systems

hosted

Linux
Unix

Linux
macOS
Windows

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Data scheme

yes

Fixed schema with schema-less datatypes (dynamic)

yes

Typing

predefined data types such as float or date

yes

Numeric data only

yes

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

yes

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

yes

SQL

Support of SQL

yes

SQL-like query language

Kusto Query Language (KQL), SQL subset

yes

with proprietary extensions

APIs and other access methods

ADO.NET
JDBC
ODBC

HTTP API
Sockets

gRPC
HTTP REST
JDBC
MQTT (Message Queue Telemetry Transport)
ODBC

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

ADO.NET
JDBC
ODBC
Proprietary native 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

JavaScript (Node.js)
Python

C
C#
C++
Go
Java
JavaScript
PHP

via ODBC
Python
R

via ODBC
Scala

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

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

Server-side scripts

Stored procedures

yes

Yes, possible languages: KQL, Python, R

yes

proprietary syntax

Triggers

yes

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

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

Implicit feature of the cloud service

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

none

selectable replication factor

yes

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

Multi-source replication
Source-replica replication

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

none

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

not for MyISAM storage engine

Concurrency

Support for concurrent manipulation of data

yes

locking

yes

table locks or row locks depending on storage engine

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

volatile and lookup table

yes

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

Azure Active Directory Authentication

Users with fine-grained authorization concept

no user groups or roles

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.