DBMS > Apache Drill vs. Microsoft Azure SQL Database vs. YTsaurus

System Properties Comparison Apache Drill vs. Microsoft Azure SQL Database vs. YTsaurus

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Editorial information provided by DB-Engines

Name

Description

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

Database as a Service offering with high compatibility to Microsoft SQL Server

YTsaurus is an open source platform for distributed storage and processing.

Primary database model

Document store
Relational DBMS

Relational DBMS

Document store
Key-value store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	1.90
Rank	#126	Overall
	#23	Document stores
	#60	Relational DBMS

Score	72.95
Rank	#16	Overall
	#11	Relational DBMS

Score	0.15
Rank	#323	Overall
	#44	Document stores
	#47	Key-value stores

Website

drill.apache.org

azure.microsoft.com/en-us/products/azure-sql/database

ytsaurus.tech

Technical documentation

drill.apache.org/docs

docs.microsoft.com/en-us/azure/azure-sql

ytsaurus.tech/docs/en

Developer

Apache Software Foundation

Microsoft

Yandex

Initial release

2012

2010

2023

Current release

1.20.3, January 2023

V12

License

Commercial or Open Source

Open Source

Apache Version 2

commercial

Open Source

Apache License, Version 2.0

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

C++

Server operating systems

Linux
OS X
Windows

hosted

Ubuntu

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

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

yes

SQL

Support of SQL

SQL SELECT statement is SQL:2003 compliant

yes

YQL, an SQL-based language, is supported

APIs and other access methods

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

Supported programming languages

C++

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

C++
Go
Java
JavaScript
Python

Server-side scripts

Stored procedures

user defined functions

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes, with always 3 replicas available

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

none

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

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

fine grained access rights according to SQL-standard

Access Control Lists

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Recent citations in the news

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

Analyse Kafka messages with SQL queries using Apache Drill
27 September 2019, Towards Data Science

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30 January 2019, Business Wire

Apache Drill Adds New Data Formats
28 March 2022, iProgrammer

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11 April 2016, The New Stack

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