DBMS > Amazon Redshift vs. AntDB vs. Apache Kylin vs. Netezza

System Properties Comparison Amazon Redshift vs. AntDB vs. Apache Kylin 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

A scalable, multi-tenant, MPP-architectured RDBMS for OLTP and OLAP operations, highly compatible with Oracle

A distributed analytics engine for big data, providing a SQL interface and multi-dimensional analysis (OLAP) and leveraging the Hadoop stack

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Relational DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.23
Rank	#317	Overall
	#141	Relational DBMS

Score	1.25
Rank	#170	Overall
	#77	Relational DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Website

aws.amazon.com/redshift

www.asiainfo.com/en_us/product_aisware_antdb_detail.html

kylin.apache.org

www.ibm.com/products/netezza

Technical documentation

docs.aws.amazon.com/redshift

kylin.apache.org/docs

Developer

Amazon (based on PostgreSQL)

AsiaInfo Technologies Limited

Apache Software Foundation, originally contributed from eBay Inc

IBM

Initial release

2012

2015

2000

Current release

3.1.0, July 2020

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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

Java

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

SQL2016 compliant

ANSI SQL for queries (using Apache Calcite)

yes

APIs and other access methods

JDBC
ODBC

JDBC
MySQL protocol compliant
ODBC

JDBC
ODBC
RESTful HTTP API

JDBC
ODBC
OLE DB

Supported programming languages

All languages supporting JDBC/ODBC

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

user defined functions

in Python

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

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

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

Users with fine-grained authorization concept

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