DBMS > Apache Druid vs. Microsoft Azure SQL Database vs. XTDB

System Properties Comparison Apache Druid vs. Microsoft Azure SQL Database vs. XTDB

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Editorial information provided by DB-Engines

Name

Description

Open-source analytics data store designed for sub-second OLAP queries on high dimensionality and high cardinality data

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

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Document store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

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

Score	3.34
Rank	#88	Overall
	#48	Relational DBMS
	#7	Time Series DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	0.11
Rank	#343	Overall
	#46	Document stores

Website

druid.apache.org

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

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

druid.apache.org/docs/latest/design

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

www.xtdb.com/docs

Developer

Apache Software Foundation and contributors

Microsoft

Juxt Ltd.

Initial release

2012

2010

2019

Current release

29.0.1, April 2024

V12

1.19, September 2021

License

Commercial or Open Source

Open Source

Apache license v2

commercial

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

C++

Clojure

Server operating systems

Linux
OS X
Unix

hosted

All OS with a Java 8 (and higher) VM
Linux

Data scheme

yes

schema-less columns are supported

yes

schema-free

Typing

predefined data types such as float or date

yes

yes, extensible-data-notation format

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 for querying

yes

limited SQL, making use of Apache Calcite

APIs and other access methods

JDBC
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

HTTP REST
JDBC

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

Clojure
Java

Server-side scripts

Stored procedures

Transact SQL

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes, via HDFS, S3 or other storage engines

yes, with always 3 replicas available

yes, each node contains all data

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

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

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

User concepts

Access control

RBAC using LDAP or Druid internals for users and groups for read/write by datasource and system

fine grained access rights according to SQL-standard

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Recent citations in the news

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