DBMS > Amazon Redshift vs. Microsoft Azure SQL Database vs. MonetDB vs. Realm vs. Stardog

System Properties Comparison Amazon Redshift vs. Microsoft Azure SQL Database vs. MonetDB vs. Realm vs. Stardog

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

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

A relational database management system that stores data in columns

A DBMS built for use on mobile devices that’s a fast, easy to use alternative to SQLite and Core Data

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Primary database model

Relational DBMS

Document store

Graph DBMS
RDF store

Secondary database models

Document store
Graph DBMS
Spatial DBMS

Document store
Spatial DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	77.99
Rank	#16	Overall
	#11	Relational DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	7.60
Rank	#52	Overall
	#9	Document stores

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Website

aws.amazon.com/redshift

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

www.monetdb.org

realm.io

www.stardog.com

Technical documentation

docs.aws.amazon.com/redshift

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

www.monetdb.org/Documentation

realm.io/docs

docs.stardog.com

Developer

Amazon (based on PostgreSQL)

Microsoft

MonetDB BV

Realm, acquired by MongoDB in May 2019

Stardog-Union

Initial release

2012

2010

2004

2014

2010

Current release

V12

Dec2023 (11.49), December 2023

7.3.0, May 2020

License

Commercial or Open Source

commercial

Open Source

Mozilla Public License 2.0

Open Source

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

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++

Java

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Android
Backend: server-less
iOS
Windows

Linux
macOS
Windows

Data scheme

yes

schema-free and OWL/RDFS-schema support

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

Import/export of XML data possible

Secondary indexes

restricted

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL 2003 with some extensions

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

Supported programming languages

All languages supporting JDBC/ODBC

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

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

.Net
Java

with Android only
Objective-C
React Native
Swift

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

in Python

Transact SQL

yes, in SQL, C, R

runs within the applications so server-side scripts are unnecessary

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes

Change Listeners

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding via remote tables

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

yes, with always 3 replicas available

none

Source-replica replication available in experimental status

none

Multi-source replication in HA-Cluster

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

yes

relationships in graphs

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

In-Memory realm

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes

Access rights for users and roles

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