DBMS > Amazon Redshift vs. MonetDB vs. NuoDB vs. TDengine

System Properties Comparison Amazon Redshift vs. MonetDB vs. NuoDB vs. TDengine

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

A relational database management system that stores data in columns

NuoDB is a webscale distributed database that supports SQL and ACID transactions

Time Series DBMS and big data platform

Primary database model

Relational DBMS

Time Series DBMS

Secondary database models

Document store
Spatial DBMS

Relational DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.72
Rank	#145	Overall
	#67	Relational DBMS

Score	0.89
Rank	#198	Overall
	#92	Relational DBMS

Score	2.60
Rank	#107	Overall
	#8	Time Series DBMS

Website

aws.amazon.com/redshift

www.monetdb.org

www.3ds.com/nuodb-distributed-sql-database

github.com/taosdata/TDengine
tdengine.com

Technical documentation

docs.aws.amazon.com/redshift

www.monetdb.org/Documentation

doc.nuodb.com

docs.tdengine.com

Developer

Amazon (based on PostgreSQL)

MonetDB BV

Dassault Systèmes

originally NuoDB, Inc.

TDEngine, previously Taos Data

Initial release

2012

2004

2013

2019

Current release

Dec2023 (11.49), December 2023

3.0, August 2022

License

Commercial or Open Source

commercial

Open Source

Mozilla Public License 2.0

commercial

limited edition free

Open Source

AGPL V3, also commercial editions 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++

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

hosted

Amazon EC2, Windows Azure, SoftLayer
Linux
OS X
Windows

Linux
Windows

Data scheme

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL 2003 with some extensions

yes

Standard SQL with extensions for time-series applications

APIs and other access methods

JDBC
ODBC

JDBC
native C library

MAPI library (MonetDB application programming interface)
ODBC

ADO.NET
JDBC
ODBC

JDBC
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

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

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

C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Rust

Server-side scripts

Stored procedures

user defined functions

in Python

yes, in SQL, C, R

Java, SQL

Triggers

yes

yes, via alarm monitoring

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding via remote tables

data is dynamically stored/cached on the nodes where it is read/written

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication available in experimental status

yes

Managed transparently by NuoDB

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

informational only, not enforced by the system

yes

Transaction concepts

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

ACID

tunable commit protocol

Concurrency

Support for concurrent manipulation of data

yes

MVCC

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

Temporary table

User concepts

Access control

fine grained access rights according to SQL-standard

Standard SQL roles/ privileges, Administrative Users

yes

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Market metrics

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Licensing and pricing models

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