DBMS > Amazon Redshift vs. GBase vs. Netezza vs. Oracle Coherence

System Properties Comparison Amazon Redshift vs. GBase vs. Netezza vs. Oracle Coherence

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Widely used RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Data warehouse and analytics appliance part of IBM PureSystems

Oracles in-memory data grid solution

Primary database model

Relational DBMS

Key-value store

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	1.92
Rank	#130	Overall
	#22	Key-value stores

Website

aws.amazon.com/redshift

www.gbase.cn

www.ibm.com/products/netezza

www.oracle.com/java/coherence

Technical documentation

docs.aws.amazon.com/redshift

docs.oracle.com/en/middleware/standalone/coherence

Developer

Amazon (based on PostgreSQL)

General Data Technology Co., Ltd.

IBM

Oracle

Initial release

2012

2004

2000

2007

Current release

GBase 8a, GBase 8s, GBase 8c

14.1, August 2023

License

Commercial or Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

C, Java, Python

Java

Server operating systems

hosted

Linux

included in appliance

All OS with a Java VM

Data scheme

yes

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.

yes

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

Standard with numerous extensions

yes

APIs and other access methods

JDBC
ODBC

ADO.NET
C API
JDBC
ODBC

JDBC
ODBC
OLE DB

JCache
JPA
RESTful HTTP API

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Fortran
Java
Lua
Perl
Python
R

.Net
C++
Java

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

yes

Triggers

yes

Live Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash) and vertical partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

yes, with selectable consistency level

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

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

configurable

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

optionally

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

Users with fine-grained authorization concept

authentification to access the cache via certificates or http basic authentication

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