DBMS > Amazon Redshift vs. GBase vs. HBase vs. Netezza

System Properties Comparison Amazon Redshift vs. GBase vs. HBase vs. Netezza

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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.

Wide-column store based on Apache Hadoop and on concepts of BigTable

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Relational DBMS

Wide column store

Relational DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	1.07
Rank	#185	Overall
	#86	Relational DBMS

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Website

aws.amazon.com/redshift

www.gbase.cn

hbase.apache.org

www.ibm.com/products/netezza

Technical documentation

docs.aws.amazon.com/redshift

hbase.apache.org/book.html

Developer

Amazon (based on PostgreSQL)

General Data Technology Co., Ltd.

Apache Software Foundation

Apache top-level project, originally developed by Powerset

IBM

Initial release

2012

2004

2008

2000

Current release

GBase 8a, GBase 8s, GBase 8c

2.3.4, January 2021

License

Commercial or Open Source

commercial

Open Source

Apache version 2

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

Linux
Unix
Windows

using Cygwin

Linux

included in appliance

Data scheme

yes

schema-free, schema definition possible

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

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

Java API
RESTful HTTP API
Thrift

JDBC
ODBC
OLE DB

Supported programming languages

All languages supporting JDBC/ODBC

C
C#
C++
Groovy
Java
PHP
Python
Scala

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

yes

Coprocessors in Java

yes

Triggers

yes

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

Multi-source replication
Source-replica replication

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

Immediate Consistency or Eventual 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

Single row ACID (across millions of columns)

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

yes

Access Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

Users with fine-grained authorization concept

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