DBMS > Apache Druid vs. Microsoft Azure SQL Database vs. Microsoft SQL Server vs. Rockset vs. searchxml

System Properties Comparison Apache Druid vs. Microsoft Azure SQL Database vs. Microsoft SQL Server vs. Rockset vs. searchxml

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

Microsofts flagship relational DBMS

A scalable, reliable search and analytics service in the cloud, built on RocksDB

DBMS for structured and unstructured content wrapped with an application server

Primary database model

Relational DBMS
Time Series DBMS

Relational DBMS

Document store

Native XML DBMS
Search engine

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Relational DBMS
Search engine

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	824.29
Rank	#3	Overall
	#3	Relational DBMS

Score	0.79
Rank	#211	Overall
	#35	Document stores

Score	0.00
Rank	#383	Overall
	#7	Native XML DBMS
	#25	Search engines

Website

druid.apache.org

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

www.microsoft.com/en-us/sql-server

rockset.com

www.searchxml.net/category/products

Technical documentation

druid.apache.org/docs/latest/design

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

learn.microsoft.com/en-US/sql/sql-server

docs.rockset.com

www.searchxml.net/support/handouts

Developer

Apache Software Foundation and contributors

Microsoft

Rockset

informationpartners gmbh

Initial release

2012

2010

1989

2019

2015

Current release

29.0.1, April 2024

V12

SQL Server 2022, November 2022

1.0

License

Commercial or Open Source

Open Source

Apache license v2

commercial

restricted free version is available

commercial

Cloud-based only

Only available as a cloud service

yes

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Database as a Service

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Implementation language

Java

C++

Server operating systems

Linux
OS X
Unix

hosted

Linux
Windows

hosted

Windows

Data scheme

yes

schema-less columns are supported

yes

schema-free

Typing

predefined data types such as float or date

yes

dynamic typing

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

ingestion from XML files supported

yes

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

SQL for querying

yes

Read-only SQL queries, including JOINs

APIs and other access methods

JDBC
RESTful HTTP/JSON API

ADO.NET
JDBC
ODBC

ADO.NET
JDBC
ODBC
OLE DB
Tabular Data Stream (TDS)

HTTP REST

RESTful HTTP API
WebDAV
XQuery
XSLT

Supported programming languages

Clojure
JavaScript
PHP
Python
R
Ruby
Scala

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

C#
C++
Delphi
Go
Java
JavaScript (Node.js)
PHP
Python
R
Ruby
Visual Basic

Go
Java
JavaScript (Node.js)
Python

C++

most other programming languages supported via APIs

Server-side scripts

Stored procedures

Transact SQL

Transact SQL, .NET languages, R, Python and (with SQL Server 2019) Java

yes

on the application server

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

manual/auto, time-based

tables can be distributed across several files (horizontal partitioning); sharding through federation

Automatic sharding

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, but depending on the SQL-Server Edition

yes

sychronisation to multiple collections

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

multiple readers, single writer

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

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

Access rights for users and organizations can be defined via Rockset console

Domain, group and role-based access control at the document level and for application services

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