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	0.35
Rank	#282	Overall
	#25	Time Series DBMS

Score	98.83
Rank	#12	Overall
	#1	Wide column stores

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Score	0.74
Rank	#224	Overall
	#103	Relational DBMS

Website

axibase.com/docs/atsd/finance

cassandra.apache.org

azure.microsoft.com/services/data-explorer

sqream.com

Technical documentation

cassandra.apache.org/doc/latest

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

docs.sqream.com

Developer

Axibase Corporation

Apache Software Foundation

Apache top level project, originally developped by Facebook

Microsoft

SQream Technologies

Initial release

2013

2008

2019

2017

Current release

15585

4.1.3, July 2023

cloud service with continuous releases

2022.1.6, December 2022

License

Commercial or Open Source

commercial

Community Edition (single node) is free, Enterprise Edition (distributed) is paid

Open Source

Apache version 2

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.

Astra DB: Multi-cloud DBaaS built on Apache Cassandra.

Implementation language

Java

C++, CUDA, Haskell, Java, Scala

Server operating systems

Linux

BSD
Linux
OS X
Windows

hosted

Linux

Data scheme

yes

schema-free

Fixed schema with schema-less datatypes (dynamic)

yes

Typing

predefined data types such as float or date

yes

short, integer, long, float, double, decimal, string

yes

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

yes, ANSI Standard SQL 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

restricted

only equality queries, not always the best performing solution

all fields are automatically indexed

SQL

Support of SQL

SQL-like query language

SQL-like SELECT, DML and DDL statements (CQL)

Kusto Query Language (KQL), SQL subset

yes

APIs and other access methods

JDBC
Proprietary protocol (Network API)
RESTful HTTP API

Proprietary protocol

CQL (Cassandra Query Language, an SQL-like language)
Thrift

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

.Net
JDBC
ODBC

Supported programming languages

Go
Java
PHP
Python
R
Ruby

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

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

C++
Java
JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes

Yes, possible languages: KQL, Python, R

user defined functions in Python

Triggers

yes

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

no "single point of failure"

Sharding

Implicit feature of the cloud service

horizontal and vertical partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

selectable replication factor

Representation of geographical distribution of servers is possible

yes

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

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency
Immediate Consistency

can be individually decided for each write operation

Eventual Consistency
Immediate Consistency

Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Atomicity and isolation are supported for single operations

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.

User concepts

Access control

Access rights for users can be defined per object

Azure Active Directory Authentication

More information provided by the system vendor

Specific characteristics

Apache Cassandra is the leading NoSQL, distributed database management system, well...
» more

Competitive advantages

No single point of failure ensures 100% availability . Operational simplicity for...
» more

Typical application scenarios

Internet of Things (IOT), fraud detection applications, recommendation engines, product...
» more

Key customers

Apple, Netflix, Uber, ING,, Intuit,Fidelity, NY Times, Outbrain, BazaarVoice, Best...
» more

Market metrics

Cassandra is used by 40% of the Fortune 100.
» more

Licensing and pricing models

Apache licenseÂ Pricing for commercial distributions provided by DataStax and available...
» more

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