DBMS > Microsoft Azure AI Search vs. Microsoft SQL Server vs. MonetDB vs. Rockset vs. Sadas Engine

System Properties Comparison Microsoft Azure AI Search vs. Microsoft SQL Server vs. MonetDB vs. Rockset vs. Sadas Engine

Editorial information provided by DB-Engines

Name

Description

Search-as-a-service for web and mobile app development

Microsofts flagship relational DBMS

A relational database management system that stores data in columns

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

SADAS Engine is a columnar DBMS specifically designed for high performance in data warehouse environments

Primary database model

Secondary database models

Vector DBMS

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

Relational DBMS
Search engine

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

Score	5.75
Rank	#58	Overall
	#7	Search engines

Score	807.76
Rank	#3	Overall
	#3	Relational DBMS

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Score	1.07
Rank	#180	Overall
	#31	Document stores

Score	0.00
Rank	#385	Overall
	#159	Relational DBMS

Website

azure.microsoft.com/en-us/services/search

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

www.monetdb.org

rockset.com

www.sadasengine.com

Technical documentation

learn.microsoft.com/en-us/azure/search

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

www.monetdb.org/Documentation

docs.rockset.com

www.sadasengine.com/en/sadas-engine-download-free-trial-and-documentation/#documentation

Developer

Microsoft

MonetDB BV

Rockset

SADAS s.r.l.

Initial release

2015

1989

2004

2019

2006

Current release

SQL Server 2022, November 2022

Dec2023 (11.49), December 2023

8.0

License

Commercial or Open Source

commercial

restricted free version is available

Open Source

Mozilla Public License 2.0

commercial

free trial version available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

C++

Server operating systems

hosted

Linux
Windows

FreeBSD
Linux
OS X
Solaris
Windows

hosted

AIX
Linux
Windows

Data scheme

yes

schema-free

yes

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

Secondary indexes

yes

all fields are automatically indexed

yes

SQL

Support of SQL

yes

SQL 2003 with some extensions

Read-only SQL queries, including JOINs

yes

APIs and other access methods

RESTful HTTP API

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

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

HTTP REST

JDBC
ODBC
Proprietary protocol

Supported programming languages

C#
Java
JavaScript
Python

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

C
C++
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby

Go
Java
JavaScript (Node.js)
Python

.Net
C
C#
C++
Groovy
Java
PHP
Python

Server-side scripts

Stored procedures

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

yes, in SQL, C, R

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

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

Sharding via remote tables

Automatic sharding

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Implicit feature of the cloud service

yes, but depending on the SQL-Server Edition

none

Source-replica replication available in experimental status

yes

none

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

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

managed by 'Learn by Usage'

User concepts

Access control

yes

using Azure authentication

fine grained access rights according to SQL-standard

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

Access rights for users, groups and roles according to SQL-standard

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