DBMS > Microsoft Azure SQL Database vs. OpenQM vs. Snowflake vs. SWC-DB

System Properties Comparison Microsoft Azure SQL Database vs. OpenQM vs. Snowflake vs. SWC-DB

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

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

QpenQM is a high-performance, self-tuning, multi-value DBMS

Cloud-based data warehousing service for structured and semi-structured data

A high performance, scalable Wide Column DBMS

Primary database model

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Time Series DBMS

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

Score	76.78
Rank	#16	Overall
	#11	Relational DBMS

Score	0.34
Rank	#284	Overall
	#10	Multivalue DBMS

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Score	0.08
Rank	#364	Overall
	#13	Wide column stores

Website

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

www.rocketsoftware.com/products/rocket-multivalue-application-development-platform/rocket-open-qm

www.snowflake.com

github.com/kashirin-alex/swc-db
www.swcdb.org

Technical documentation

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

docs.snowflake.net/manuals/index.html

Developer

Microsoft

Rocket Software, originally Martin Phillips

Snowflake Computing Inc.

Alex Kashirin

Initial release

2010

1993

2014

2020

Current release

V12

3.4-12

0.5, April 2021

License

Commercial or Open Source

commercial

Open Source

GPLv2, extended commercial license available

commercial

Open Source

GPL V3

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

hosted

AIX
FreeBSD
Linux
macOS
Raspberry Pi
Solaris
Windows

hosted

Linux

Data scheme

yes

with some exceptions

yes

support of semi-structured data formats (JSON, XML, Avro)

schema-free

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

yes

SQL-like query language

APIs and other access methods

ADO.NET
JDBC
ODBC

CLI Client
JDBC
ODBC

Proprietary protocol
Thrift

Supported programming languages

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

.Net
Basic
C
Java
Objective C
PHP
Python

JavaScript (Node.js)
Python

C++

Server-side scripts

Stored procedures

Transact SQL

yes

user defined functions

Triggers

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

yes

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

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

In-memory capabilities

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights can be defined down to the item level

Users with fine-grained authorization concept, user roles and pluggable authentication

More information provided by the system vendor

We invite representatives of system vendors to contact us for updating and extending the system information,
and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.