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	2.37
Rank	#110	Overall
	#54	Relational DBMS

Score	2.91
Rank	#93	Overall
	#3	RDF stores

Score	1.56
Rank	#141	Overall
	#4	Native XML DBMS

Score	3.28
Rank	#83	Overall
	#45	Relational DBMS

Website

www.4d.com

jena.apache.org/documentation/tdb/index.html

basex.org

azure.microsoft.com/services/data-explorer

Technical documentation

developer.4d.com

jena.apache.org/documentation/tdb/index.html

docs.basex.org

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

Developer

4D, Inc

Apache Software Foundation

originally developed by HP Labs

BaseX GmbH

Microsoft

Initial release

1984

2000

2007

2019

Current release

v20, April 2023

4.9.0, July 2023

11.2, August 2024

cloud service with continuous releases

License

Commercial or Open Source

commercial

Open Source

Apache License, Version 2.0

Open Source

BSD license

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

Server operating systems

OS X
Windows

All OS with a Java VM

Linux
OS X
Windows

hosted

Data scheme

yes

RDF Schemas

schema-free

Fixed schema with schema-less datatypes (dynamic)

Typing

predefined data types such as float or date

yes

XQuery supports types

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

close to SQL 92

Kusto Query Language (KQL), SQL subset

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

Fuseki

REST-style SPARQL HTTP Interface
Jena RDF API
RIO

RDF Input/Output

Java API
RESTful HTTP API
RESTXQ
WebDAV
XML:DB
XQJ

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

Supported programming languages

4D proprietary IDE
PHP

Java

Actionscript
C
C#
Haskell
Java
JavaScript

Node.js
Lisp
Perl
PHP
Python
Qt
Rebol
Ruby
Scala
Visual Basic

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

Server-side scripts

Stored procedures

yes

Yes, possible languages: KQL, Python, R

Triggers

yes

via event handler

yes

via events

yes

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

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

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

TDB Transactions

multiple readers, single writer

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

Users and groups

Access control via Jena Security

Users with fine-grained authorization concept on 4 levels

Azure Active Directory 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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

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