DBMS > Amazon Redshift vs. Microsoft Azure Synapse Analytics vs. MonetDB vs. OrientDB vs. RavenDB

System Properties Comparison Amazon Redshift vs. Microsoft Azure Synapse Analytics vs. MonetDB vs. OrientDB vs. RavenDB

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Elastic, large scale data warehouse service leveraging the broad eco-system of SQL Server

A relational database management system that stores data in columns

Multi-model DBMS (Document, Graph, Key/Value)

Open Source Operational and Transactional Enterprise NoSQL Document Database

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store

Document store

Secondary database models

Document store
Spatial DBMS

Graph DBMS
Spatial DBMS
Time Series DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	19.93
Rank	#31	Overall
	#19	Relational DBMS

Score	1.72
Rank	#141	Overall
	#64	Relational DBMS

Score	3.25
Rank	#89	Overall
	#16	Document stores
	#6	Graph DBMS
	#13	Key-value stores

Score	2.84
Rank	#101	Overall
	#18	Document stores

Website

aws.amazon.com/redshift

azure.microsoft.com/services/synapse-analytics

www.monetdb.org

orientdb.org

ravendb.net

Technical documentation

docs.aws.amazon.com/redshift

docs.microsoft.com/azure/synapse-analytics

www.monetdb.org/Documentation

www.orientdb.com/docs/last/index.html

ravendb.net/docs

Developer

Amazon (based on PostgreSQL)

Microsoft

MonetDB BV

OrientDB LTD; CallidusCloud; SAP

Hibernating Rhinos

Initial release

2012

2016

2004

2010

Current release

Dec2023 (11.49), December 2023

3.2.29, March 2024

5.4, July 2022

License

Commercial or Open Source

commercial

Open Source

Mozilla Public License 2.0

Open Source

Apache version 2

Open Source

AGPL version 3, commercial license available

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

All OS with a Java JDK (>= JDK 6)

Linux
macOS
Raspberry Pi
Windows

Data scheme

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL 2003 with some extensions

SQL-like query language, no joins

SQL-like query language (RQL)

APIs and other access methods

JDBC
ODBC

ADO.NET
JDBC
ODBC

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

.NET Client API
F# Client API
Go Client API
Java Client API
NodeJS Client API
PHP Client API
Python Client API
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

C#
Java
PHP

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

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

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

Server-side scripts

Stored procedures

user defined functions

in Python

Transact SQL

yes, in SQL, C, R

Java, Javascript

yes

Triggers

yes

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding, horizontal partitioning

Sharding via remote tables

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication available in experimental status

Multi-source replication

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Default ACID transactions on the local node (eventually consistent across the cluster). Atomic operations with cluster-wide ACID transactions. Eventual consistency for indexes and full-text search indexes.

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

docs.microsoft.com/en-us/azure/synapse-analytics/sql-data-warehouse/sql-data-warehouse-table-constraints

yes

relationship in graphs

Transaction concepts

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

ACID

ACID, Cluster-wide transaction available

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

fine grained access rights according to SQL-standard

yes

fine grained access rights according to SQL-standard

Access rights for users and roles; record level security configurable

Authorization levels configured per client per database

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