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	1.02
Rank	#189	Overall
	#88	Relational DBMS

Score	98.83
Rank	#12	Overall
	#1	Wide column stores

Score	47.91
Rank	#20	Overall
	#14	Relational DBMS

Score	3.80
Rank	#81	Overall
	#43	Relational DBMS

Website

altibase.com

cassandra.apache.org

www.claris.com/filemaker

azure.microsoft.com/services/data-explorer

Technical documentation

github.com/ALTIBASE/Documents/tree/master/Manuals

cassandra.apache.org/doc/latest

www.claris.com/resources/documentation

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

Developer

Altibase

Apache Software Foundation

Apache top level project, originally developped by Facebook

Claris

a subsidiary of Apple

Microsoft

Initial release

1999

2008

1983

2019

Current release

v7.3, 2023, August 2023

4.1.3, July 2023

19.4.1, November 2021

cloud service with continuous releases

License

Commercial or Open Source

commercial

Open source edition discontinued with March 2023

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

C++

Java

Server operating systems

AIX
HP-UX
Linux

BSD
Linux
OS X
Windows

iOS

client part only
Linux
OS X
Windows

hosted

Data scheme

yes

schema-free

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

A http query request can return the data in XML format

yes

Secondary indexes

yes

restricted

only equality queries, not always the best performing solution

yes

all fields are automatically indexed

SQL

Support of SQL

ANSI SQL-92

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

yes

via plugins

Kusto Query Language (KQL), SQL subset

APIs and other access methods

JDBC
ODBC
Proprietary protocol

Proprietary protocol

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

Filemaker WebDirect
JDBC
ODBC

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

Supported programming languages

C
C++
Java

C#
C++
Clojure
Erlang
Go
Haskell
Java
JavaScript

Node.js
Perl
PHP
Python
Ruby
Scala

PHP

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

Server-side scripts

Stored procedures

stored procedures and stored functions

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

Sharding

no "single point of failure"

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

yes

selectable replication factor

Representation of geographical distribution of servers is possible

Source-replica replication, warm standby

since Version 14

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

yes

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

can be individually decided for each write operation

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomicity and isolation are supported for single operations

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

Access rights for users can be defined per object

simple rights management via user accounts and connection to external directory services

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

News

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11 June 2024

Introducing Tejas Kumar, Developer Relations Engineer
7 June 2024

Indexing All of Wikipedia on a Laptop
5 June 2024

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3 June 2024

Focus on Creativity, Not Clusters: DataStax Mission Control in Action!
30 May 2024

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