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	7.57
Rank	#51	Overall
	#32	Relational DBMS

Score	0.67
Rank	#233	Overall
	#20	Time Series DBMS

Score	0.66
Rank	#234	Overall
	#107	Relational DBMS

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

aws.amazon.com/rds/aurora

github.com/kairosdb/kairosdb

www.kinetica.com

azure.microsoft.com/services/data-explorer

www.snowflake.com

Technical documentation

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

kairosdb.github.io

docs.kinetica.com

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

docs.snowflake.net/manuals/index.html

Developer

Amazon

Kinetica

Microsoft

Snowflake Computing Inc.

Initial release

2015

2013

2012

2019

2014

Current release

1.2.2, November 2018

7.1, August 2021

cloud service with continuous releases

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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.

Implementation language

Java

C, C++

Server operating systems

hosted

Linux
OS X
Windows

Linux

hosted

Data scheme

yes

schema-free

yes

Fixed schema with schema-less datatypes (dynamic)

yes

support of semi-structured data formats (JSON, XML, Avro)

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

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

SQL

Support of SQL

yes

SQL-like DML and DDL statements

Kusto Query Language (KQL), SQL subset

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

Graphite protocol
HTTP REST
Telnet API

JDBC
ODBC
RESTful HTTP API

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

CLI Client
JDBC
ODBC

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

Java
JavaScript

Node.js
PHP
Python

C++
Java
JavaScript (Node.js)
Python

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

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

user defined functions

Yes, possible languages: KQL, Python, R

user defined functions

Triggers

yes

triggers when inserted values for one or more columns fall within a specified range

yes

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

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

based on Cassandra

Sharding

Implicit feature of the cloud service

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

based on Cassandra

Source-replica replication

yes

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

yes

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

based on Cassandra
Immediate Consistency

based on Cassandra

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate 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

GPU vRAM or System RAM

User concepts

Access control

fine grained access rights according to SQL-standard

simple password-based access control

Access rights for users and roles on table level

Azure Active Directory Authentication

Users with fine-grained authorization concept, user roles and pluggable authentication

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.