DBMS > Amazon Redshift vs. Apache Doris vs. ArcadeDB vs. Netezza

System Properties Comparison Amazon Redshift vs. Apache Doris vs. ArcadeDB 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

An MPP-based analytics DBMS embracing the MySQL protocol

Fast and scalable multi-model DBMS, originally forked from OrientDB but most of the code has been rewritten

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Relational DBMS

Document store
Graph DBMS
Key-value store
Time Series DBMS

in next version

Relational DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.57
Rank	#244	Overall
	#113	Relational DBMS

Score	0.02
Rank	#366	Overall
	#50	Document stores
	#38	Graph DBMS
	#53	Key-value stores
	#36	Time Series DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Website

aws.amazon.com/redshift

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

arcadedb.com

www.ibm.com/products/netezza

Technical documentation

docs.aws.amazon.com/redshift

github.com/apache/doris/wiki

docs.arcadedb.com

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation, originally contributed from Baidu

Arcade Data

IBM

Initial release

2012

2017

2021

2000

Current release

1.2.2, February 2023

September 2021

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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

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Implementation language

Java

Server operating systems

hosted

Linux

All OS with a Java VM

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

SQL-like query language, no joins

yes

APIs and other access methods

JDBC
ODBC

JDBC
MySQL client

JDBC
MongoDB API
OpenCypher
PostgreSQL wire protocol
Redis API
RESTful HTTP/JSON API
TinkerPop Gremlin

JDBC
ODBC
OLE DB

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

Triggers

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

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

relationship in graphs

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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