DBMS > 4D vs. Amazon Redshift vs. Databend vs. Netezza

System Properties Comparison 4D vs. Amazon Redshift vs. Databend vs. Netezza

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Editorial information provided by DB-Engines

Name

Description

Application development environment with integrated database management system

Large scale data warehouse service for use with business intelligence tools

An open-source, elastic, and workload-aware cloud data warehouse designed to meet businesses' massive-scale analytics needs at low cost and with low complexity

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	2.47
Rank	#110	Overall
	#54	Relational DBMS

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	0.34
Rank	#283	Overall
	#130	Relational DBMS

Score	8.59
Rank	#45	Overall
	#29	Relational DBMS

Website

www.4d.com

aws.amazon.com/redshift

github.com/datafuselabs/databend
www.databend.com

www.ibm.com/products/netezza

Technical documentation

developer.4d.com

docs.aws.amazon.com/redshift

docs.databend.com

Developer

4D, Inc

Amazon (based on PostgreSQL)

Databend Labs

IBM

Initial release

1984

2012

2021

2000

Current release

v20, April 2023

1.0.59, April 2023

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

Rust

Server operating systems

OS X
Windows

hosted

hosted
Linux
macOS

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.

yes

Secondary indexes

yes

restricted

yes

SQL

Support of SQL

yes

close to SQL 92

yes

does not fully support an SQL-standard

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC

CLI Client
JDBC
RESTful HTTP API

JDBC
ODBC
OLE DB

Supported programming languages

4D proprietary IDE
PHP

All languages supporting JDBC/ODBC

Go
Java
JavaScript (Node.js)
Python
Rust

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

yes

user defined functions

in Python

yes

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

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

Transaction concepts

Support to ensure data integrity after non-atomic manipulations of data

ACID

yes

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

Users and groups

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept, user roles

Users with fine-grained authorization concept

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