DBMS > Microsoft Azure Table Storage vs. MonetDB vs. OushuDB vs. SAP SQL Anywhere

System Properties Comparison Microsoft Azure Table Storage vs. MonetDB vs. OushuDB vs. SAP SQL Anywhere

Please select another system to include it in the comparison.

Editorial information provided by DB-Engines

Name

Description

A Wide Column Store for rapid development using massive semi-structured datasets

A relational database management system that stores data in columns

A data warehouse powered by Apache HAWQ supporting descriptive analysis and advanced machine learning

RDBMS database and synchronization technologies for server, desktop, remote office, and mobile environments

Primary database model

Wide column store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	3.55
Rank	#80	Overall
	#6	Wide column stores

Score	1.72
Rank	#135	Overall
	#62	Relational DBMS

Score	0.05
Rank	#357	Overall
	#151	Relational DBMS

Score	3.50
Rank	#81	Overall
	#44	Relational DBMS

Website

azure.microsoft.com/en-us/services/storage/tables

www.monetdb.org

www.oushu.com/product/oushuDB

www.sap.com/products/technology-platform/sql-anywhere.html

Technical documentation

www.monetdb.org/Documentation

www.oushu.com/documentation

help.sap.com/docs/SAP_SQL_Anywhere

Developer

Microsoft

MonetDB BV

Oushu

SAP

formerly Sybase

Initial release

2012

2004

1992

Current release

Dec2023 (11.49), December 2023

4.0.1, August 2020

17, July 2015

License

Commercial or Open Source

commercial

Open Source

Mozilla Public License 2.0

commercial

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

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux

AIX
HP-UX
Linux
OS X
Solaris
Windows

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

yes

SQL 2003 with some extensions

Full-featured ANSI SQL support

yes

APIs and other access methods

RESTful HTTP API

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

JDBC
ODBC

ADO.NET
HTTP API
JDBC
ODBC

Supported programming languages

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

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

C
C++

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

Server-side scripts

Stored procedures

yes, in SQL, C, R

yes

yes, in C/C++, Java, .Net or Perl

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Implicit feature of the cloud service

Sharding via remote tables

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

implicit feature of the cloud service. Replication either local, cross-facility or geo-redundant.

none

Source-replica replication available in experimental status

Source-replica replication

Database mirroring

MapReduce

Offers an API for user-defined Map/Reduce methods

Hadoop integration

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

optimistic locking

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

User concepts

Access control

Access rights based on private key authentication or shared access signatures

fine grained access rights according to SQL-standard

Kerberos, SSL and role based access

fine grained access rights according to SQL-standard

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.

Related products and services

We invite representatives of vendors of related products to contact us for presenting information about their offerings here.

More resources

Recent citations in the news

How to use Azure Table storage in .Net
10 July 2024, InfoWorld

Working with Azure to Use and Manage Data Lakes
23 July 2024, Simplilearn

Azure Cosmos DB Data Migration tool imports from Azure Table storage
5 May 2015, Microsoft

How to write data to Azure Table Store with an Azure Function
14 April 2017, Experts Exchange

Testing Precompiled Azure Functions Locally with Storage Emulator
8 March 2018, Visual Studio Magazine

provided by Google News

MonetDB Foundation launched
31 January 2024, Centrum Wiskunde & Informatica (CWI)

PostgreSQL, MonetDB, and Too-Big-for-Memory Data in R — Part I
6 April 2018, Data Science Central

How MonetDB/X100 Exploits Modern CPU Performance
14 January 2020, Towards Data Science

Test of Time Award for paper on vectorized execution
16 January 2024, Centrum Wiskunde & Informatica (CWI)

Monet DB The Column-Store Pioneer
4 September 2019, Open Source For You

provided by Google News

China's answer to Snowflake is shaping as data demands upgrade
8 September 2021, PingWest

provided by Google News

SAP Products & Services Data Portfolio
2 July 2021, Datamation

Securing SAP with AWS Network Firewall: Part 2 – Managed Rules
17 July 2023, AWS Blog

SAP vulnerabilities Let Attacker Inject OS Commands—Patch Now!
11 July 2023, CybersecurityNews

MindsDB is now the leading and fastest growing applied ML platform in the world
3 November 2022, PR Newswire

Gartner’s Magic Quadrant for Cloud Database Management Systems
9 December 2020, CRN

provided by Google News

Share this page