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	0.69
Rank	#226	Overall
	#37	Document stores
	#5	Spatial DBMS
	#16	Search engines
	#19	Time Series DBMS
	#11	Vector DBMS

Score	16.32
Rank	#35	Overall
	#21	Relational DBMS

Score	0.42
Rank	#261	Overall
	#120	Relational DBMS

Score	3.28
Rank	#83	Overall
	#45	Relational DBMS

Website

cratedb.com

www.ibm.com/products/informix

www.kinetica.com

azure.microsoft.com/services/data-explorer

Technical documentation

cratedb.com/docs

informix.hcldoc.com
www.ibm.com/support/knowledgecenter/SSGU8G/welcomeIfxServers.html

docs.kinetica.com

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

Developer

Crate

IBM, HCL Technologies

Effective May 1st, 2017, HCL took on development, technical support, and product management teams, and works jointly with IBM on product strategy, marketing, and sales.

Kinetica

Microsoft

Initial release

2013

1984

2012

2019

Current release

5.8.1, August 2024

14.10.FC5, November 2020

7.1, August 2021

cloud service with continuous releases

License

Commercial or Open Source

Open Source

commercial

free developer edition available

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++ and Java

C, C++

Server operating systems

All Operating Systems, including Kubernetes with CrateDB Kubernetes Operator support

AIX
HP-UX
Linux
macOS
Solaris
Windows

Linux

hosted

Data scheme

Flexible Schema (defined schema, partial schema, schema free)

yes

Fixed schema with schema-less datatypes (dynamic)

Typing

predefined data types such as float or date

yes

Since Version 12.10 support for JSON/BSON datatypes

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, but no triggers and constraints, and PostgreSQL compatibility

yes

SQL-like DML and DDL statements

Kusto Query Language (KQL), SQL subset

APIs and other access methods

ADO.NET
JDBC
ODBC
PostgreSQL wire protocol
Prometheus Remote Read/Write
RESTful HTTP API

JDBC
JSON API

MongoDB compatible
MQTT (Message Queue Telemetry Transport)
ODBC
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

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

Supported programming languages

.NET
Erlang
Go

community maintained client
Java
JavaScript (Node.js)

community maintained client
Perl

community maintained client
PHP
Python
R
Ruby

community maintained client
Scala

community maintained client

.Net
C
C++
Java
JavaScript (Node.js)
PHP
Python
Ruby

C++
Java
JavaScript (Node.js)
Python

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

Server-side scripts

Stored procedures

user defined functions (Javascript)

yes

user defined functions

Yes, possible languages: KQL, Python, R

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

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Replication methods

Methods for redundantly storing data on multiple nodes

Configurable replication on table/partition-level

Multi-source replication
Source-replica replication

Source-replica replication

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

Eventual Consistency
Read-after-write consistency on record level

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

unique row identifiers can be used for implementing an optimistic concurrency control strategy

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

rights management via user accounts

Users with fine-grained authentication, authorization, and auditing controls

Access rights for users and roles on table level

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.

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