DBMS > Microsoft Azure Data Explorer vs. PlanetScale

System Properties Comparison Microsoft Azure Data Explorer vs. PlanetScale

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Our visitors often compare Microsoft Azure Data Explorer and PlanetScale with PostgreSQL, ClickHouse and MySQL.

Editorial information provided by DB-Engines

Name

Description

Fully managed big data interactive analytics platform

Scalable, distributed, serverless MySQL database platform built on top of Vitess

Primary database model

Relational DBMS

column oriented

Relational DBMS

Secondary database models

Document store

If a column is of type dynamic docs.microsoft.com/en-us/azure/kusto/query/scalar-data-types/dynamic then it's possible to add arbitrary JSON documents in this cell
Event Store

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

Document store
Spatial DBMS

DB-Engines Ranking measures the popularity of database management systems
Trend Chart

Score	3.00
Rank	#86	Overall
	#47	Relational DBMS

Score	1.05
Rank	#180	Overall
	#80	Relational DBMS

Website

azure.microsoft.com/services/data-explorer

planetscale.com

Technical documentation

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

planetscale.com/docs

Developer

Microsoft

PlanetScale

Initial release

2019

2020

Current release

cloud service with continuous releases

License

Commercial or Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Server operating systems

hosted

Docker
Linux
macOS

Data scheme

Fixed schema with schema-less datatypes (dynamic)

yes

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

all fields are automatically indexed

yes

SQL

Support of SQL

Kusto Query Language (KQL), SQL subset

yes

with proprietary extensions

APIs and other access methods

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

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

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

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

Yes, possible languages: KQL, Python, R

yes

proprietary syntax

Triggers

yes

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

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Multi-source replication
Source-replica replication

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
Immediate Consistency

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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

Azure Active Directory Authentication

Users with fine-grained authorization concept

no user groups or roles

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More resources

Recent citations in the news

Universal Destinations & Experiences proactively improves guest satisfaction with Azure Data Explorer
14 February 2025, Microsoft

Log and Telemetry Analytics Performance Benchmark
16 August 2022, Gigaom

Azure Data Explorer: Log and telemetry analytics benchmark
16 August 2022, Microsoft Azure

Azure Data Explorer Supports Native Ingestion from Amazon S3
7 September 2022, infoq.com

Azure Data Explorer gets new engine, numerous enhancements and Synapse integration
14 October 2020, ZDNET

provided by Google News

PlanetScale Vectors Now GA: MySQL's Missing Feature?
12 April 2025, infoq.com

PlanetScale ends free tier bid, sheds staff in profitability bid
11 March 2024, theregister.com

PlanetScale raises $50M Series C as its enterprise database service hits general availability
16 November 2021, TechCrunch

PlanetScale Announces $30M Series B Funding to Accelerate Adoption of Instantly Provisioned and Infinitely Scalable Database
23 June 2021, Business Wire

PlanetScale CEO on Cloud-Prem and Climbing the Engineering Ladder
2 August 2022, future.com

provided by Google News

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