DBMS > Amazon Aurora vs. EXASOL vs. Netezza vs. PostGIS

System Properties Comparison Amazon Aurora vs. EXASOL vs. Netezza vs. PostGIS

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Editorial information provided by DB-Engines

Name

Description

MySQL and PostgreSQL compatible cloud service by Amazon

High-performance, in-memory, MPP database specifically designed for in-memory analytics.

Data warehouse and analytics appliance part of IBM PureSystems

Spatial extension of PostgreSQL

Primary database model

Relational DBMS

Spatial DBMS

Secondary database models

Document store

Relational DBMS

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

Score	7.84
Rank	#44	Overall
	#28	Relational DBMS

Score	1.66
Rank	#138	Overall
	#64	Relational DBMS

Score	7.56
Rank	#48	Overall
	#31	Relational DBMS

Score	20.16
Rank	#29	Overall
	#1	Spatial DBMS

Website

aws.amazon.com/rds/aurora

www.exasol.com

www.ibm.com/products/netezza

postgis.net

Technical documentation

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

www.exasol.com/resources

postgis.net/documentation

Developer

Amazon

Exasol

IBM

Initial release

2015

2000

2005

Current release

3.4.2, February 2024

License

Commercial or Open Source

commercial

Open Source

GPL v2.0

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

Linux

included in appliance

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

ADO.NET
JDBC
ODBC

.Net
JDBC
ODBC
WebSocket

JDBC
ODBC
OLE DB

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

Java
Lua
Python
R

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

yes

user defined functions

yes

user defined functions

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

Sharding

yes

based on PostgreSQL

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

yes

based on PostgreSQL

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Hadoop integration

yes

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

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, groups and roles according to SQL-standard

Users with fine-grained authorization concept

yes

based on PostgreSQL

More information provided by the system vendor

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

The popularity of cloud-based DBMSs has increased tenfold in four years
7 February 2017, Matthias Gelbmann

Amazon - the rising star in the DBMS market
3 August 2015, Matthias Gelbmann

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Spatial database management systems
6 April 2021, Matthias Gelbmann

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Recent citations in the news

Migrate SQL Server databases to Babelfish for Aurora PostgreSQL using change tracking with a linked server
24 September 2024, AWS Blog

Replace Amazon QLDB with Amazon Aurora PostgreSQL for audit use cases
18 July 2024, AWS Blog

Build generative AI applications with Amazon Aurora and Amazon Bedrock Knowledge Bases
2 February 2024, AWS Blog

Review your Amazon Aurora and Amazon RDS security configuration with Prowler’s new checks
6 August 2024, AWS Blog

Continuously replicate Amazon DynamoDB changes to Amazon Aurora PostgreSQL using AWS Lambda
14 May 2024, AWS Blog

provided by Google News

Exasol gets jolt of AI with Espresso suite of capabilities
26 February 2024, TechTarget

Exasol Finds AI Underinvestment Leads to Business Failure, But Data Challenges Stall Rapid Adoption
14 May 2024, insideBIGDATA

Mathias Golombek, Chief Technology Officer of Exasol – Interview Series
21 May 2024, Unite.AI

WashTec: Data Analytics for optimizing car wash systems.
27 May 2024, all-about-industries.com

It’s Back to the Database Future for Exasol CEO Tewes
26 October 2023, Datanami

provided by Google News

Unify and share data across Netezza and watsonx.data for new generative AI applications
21 June 2024, ibm.com

How to migrate a large data warehouse from IBM Netezza to Amazon Redshift with no downtime
21 August 2019, AWS Blog

AWS and IBM Netezza come out in support of Iceberg in table format face-off
1 August 2023, The Register

Copy data from Netezza to Azure with Azure Data Factory
9 September 2019, Microsoft

IBM Completes Acquisition of Netezza
11 November 2010, PR Newswire

provided by Google News

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