DBMS > Amazon Aurora vs. Amazon DocumentDB vs. Amazon Redshift

System Properties Comparison Amazon Aurora vs. Amazon DocumentDB vs. Amazon Redshift

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Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

Fast, scalable, highly available, and fully managed MongoDB-compatible database service

Large scale data warehouse service for use with business intelligence tools

Primary database model

Relational DBMS

Document store

Relational DBMS

Secondary database models

Document store

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

Score	8.18
Rank	#44	Overall
	#28	Relational DBMS

Score	1.88
Rank	#124	Overall
	#22	Document stores

Score	15.10
Rank	#38	Overall
	#23	Relational DBMS

Website

aws.amazon.com/rds/aurora

aws.amazon.com/documentdb

aws.amazon.com/redshift

Technical documentation

docs.aws.amazon.com/AmazonRDS/latest/AuroraUserGuide/CHAP_Aurora.html

aws.amazon.com/documentdb/resources

docs.aws.amazon.com/redshift

Developer

Amazon

Amazon (based on PostgreSQL)

Initial release

2015

2019

2012

License

Commercial or Open Source

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

Data scheme

yes

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

restricted

SQL

Support of SQL

yes

does not fully support an SQL-standard

APIs and other access methods

ADO.NET
JDBC
ODBC

proprietary protocol using JSON (MongoDB compatible)

JDBC
ODBC

Supported programming languages

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Go
Java
JavaScript (Node.js)
PHP
Python

All languages supporting JDBC/ODBC

Server-side scripts

Stored procedures

yes

user defined functions

in Python

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

Multi-availability zones for high availability, asynchronous replication for up to 15 read replicas

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

may be implemented via Amazon Elastic MapReduce (Amazon EMR)

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

typically not used, however similar functionality with DBRef possible

yes

informational only, not enforced by the system

Transaction concepts

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

ACID

Atomic single-document operations

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

fine grained access rights according to SQL-standard

Access rights for users and roles

fine grained access rights according to SQL-standard

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