DBMS > Apache Drill vs. Microsoft Azure Data Explorer

System Properties Comparison Apache Drill vs. Microsoft Azure Data Explorer

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Editorial information provided by DB-Engines

Name

Description

Schema-free SQL Query Engine for Hadoop, NoSQL and Cloud Storage

Fully managed big data interactive analytics platform

Primary database model

Document store
Relational DBMS

Relational DBMS

column oriented

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

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

Score	1.89
Rank	#122	Overall
	#22	Document stores
	#58	Relational DBMS

Score	3.00
Rank	#86	Overall
	#47	Relational DBMS

Website

drill.apache.org

azure.microsoft.com/services/data-explorer

Technical documentation

drill.apache.org/docs

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

Developer

Apache Software Foundation

Microsoft

Initial release

2012

2019

Current release

1.20.3, January 2023

cloud service with continuous releases

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Server operating systems

Linux
OS X
Windows

hosted

Data scheme

schema-free

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

Secondary indexes

all fields are automatically indexed

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

Kusto Query Language (KQL), SQL subset

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

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

Supported programming languages

C++

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

Server-side scripts

Stored procedures

user defined functions

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

Implicit feature of the cloud service

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.

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

none

Eventual Consistency
Immediate Consistency

Foreign keys

Referential integrity

Transaction concepts

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

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

Depending on the underlying data source

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

Depending on the underlying data source

User concepts

Access control

Depending on the underlying data source

Azure Active Directory Authentication

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More resources

Recent citations in the news

Apache Drill vs. Apache Spark – Which SQL query engine is better for you?
23 September 2019, Towards Data Science

Apache Drill improves big data SQL query engine
31 August 2021, TechTarget

Apache Drill case study: A tutorial on processing CSV files
9 June 2016, theserverside.com

MapR Advances Support for Flexible and High Performance Analytics on JSON and S3 Data with Apache Drill
30 January 2019, Business Wire

Drill Mines Diverse Data Sets, Google Style
20 May 2015, The Next Platform

provided by Google 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

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