DBMS > Amazon Redshift vs. Amazon SimpleDB vs. EsgynDB vs. Ingres vs. Netezza

System Properties Comparison Amazon Redshift vs. Amazon SimpleDB vs. EsgynDB vs. Ingres vs. Netezza

Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Hosted simple database service by Amazon, with the data stored in the Amazon Cloud.

There is an unrelated product called SimpleDB developed by Edward Sciore

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Well established RDBMS

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Relational DBMS

Key-value store

Relational DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	1.88
Rank	#133	Overall
	#23	Key-value stores

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Website

aws.amazon.com/redshift

aws.amazon.com/simpledb

www.esgyn.cn

www.actian.com/databases/ingres

www.ibm.com/products/netezza

Technical documentation

docs.aws.amazon.com/redshift

docs.aws.amazon.com/simpledb

docs.actian.com/ingres

Developer

Amazon (based on PostgreSQL)

Amazon

Esgyn

Actian Corporation

IBM

Initial release

2012

2007

2015

1974

originally developed at University Berkely in early 1970s

2000

Current release

11.2, May 2022

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

C++, Java

Server operating systems

hosted

Linux

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

Linux

included in appliance

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.

but tools for importing/exporting data from/to XML-files available

Secondary indexes

restricted

yes

All columns are indexed automatically

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

RESTful HTTP API

ADO.NET
JDBC
ODBC

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

JDBC
ODBC
OLE DB

Supported programming languages

All languages supporting JDBC/ODBC

.Net
C
C++
Erlang
Java
PHP
Python
Ruby
Scala

All languages supporting JDBC/ODBC/ADO.Net

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

user defined functions

in Python

Java Stored Procedures

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding must be implemented in the application

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Multi-source replication between multi datacenters

Ingres Replicator

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

can be specified for read operations

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

Concurrent data updates can be detected by the application

ACID

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

User concepts

Access control

fine grained access rights according to SQL-standard

Access rights for users and roles can be defined via the AWS Identity and Access Management (IAM)

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

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