DBMS > Amazon Redshift vs. Apache Doris vs. Netezza vs. Warp 10

System Properties Comparison Amazon Redshift vs. Apache Doris vs. Netezza vs. Warp 10

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

An MPP-based analytics DBMS embracing the MySQL protocol

Data warehouse and analytics appliance part of IBM PureSystems

TimeSeries DBMS specialized on timestamped geo data based on LevelDB or HBase

Primary database model

Relational DBMS

Time Series DBMS

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Trend Chart

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.57
Rank	#244	Overall
	#113	Relational DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Score	0.07
Rank	#349	Overall
	#32	Time Series DBMS

Website

aws.amazon.com/redshift

doris.apache.org
github.com/apache/doris

www.ibm.com/products/netezza

www.warp10.io

Technical documentation

docs.aws.amazon.com/redshift

github.com/apache/doris/wiki

www.warp10.io/content/02_Getting_started

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation, originally contributed from Baidu

IBM

SenX

Initial release

2012

2017

2000

2015

Current release

1.2.2, February 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

commercial

Open Source

Apache License 2.0

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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Implementation language

Java

Server operating systems

hosted

Linux

included in appliance

Linux
OS X
Windows

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

JDBC
MySQL client

JDBC
ODBC
OLE DB

HTTP API
Jupyter
WebSocket

Supported programming languages

All languages supporting JDBC/ODBC

Java

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

user defined functions

in Python

user defined functions

yes

WarpScript

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

Source-replica replication

selectable replication factor

based on HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

based on HBase

Foreign keys

Referential integrity

yes

informational only, not enforced by the system

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

Mandatory use of cryptographic tokens, containing fine-grained authorizations

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