DBMS > 4D vs. Amazon Redshift vs. Atos Standard Common Repository vs. Hawkular Metrics

System Properties Comparison 4D vs. Amazon Redshift vs. Atos Standard Common Repository vs. Hawkular Metrics

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Editorial information provided by DB-Engines

Name

This system has been discontinued and will be removed from the DB-Engines ranking.

Description

Application development environment with integrated database management system

Large scale data warehouse service for use with business intelligence tools

Highly scalable database system, designed for managing session and subscriber data in modern mobile communication networks

Hawkular metrics is the metric storage of the Red Hat sponsored Hawkular monitoring system. It is based on Cassandra.

Primary database model

Relational DBMS

Document store
Key-value store

Time Series DBMS

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

Score	2.58
Rank	#108	Overall
	#54	Relational DBMS

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	0.00
Rank	#379	Overall
	#40	Time Series DBMS

Website

www.4d.com

aws.amazon.com/redshift

atos.net/en/convergence-creators/portfolio/standard-common-repository

www.hawkular.org

Technical documentation

developer.4d.com

docs.aws.amazon.com/redshift

www.hawkular.org/hawkular-metrics/docs/user-guide

Developer

4D, Inc

Amazon (based on PostgreSQL)

Atos Convergence Creators

Community supported by Red Hat

Initial release

1984

2012

2016

2014

Current release

v20, April 2023

1703

License

Commercial or Open Source

commercial

Open Source

Apache 2.0

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

OS X
Windows

hosted

Linux

Linux
OS X
Windows

Data scheme

yes

Schema and schema-less with LDAP views

schema-free

Typing

predefined data types such as float or date

yes

optional

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

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC

LDAP

HTTP REST

Supported programming languages

4D proprietary IDE
PHP

All languages supporting JDBC/ODBC

All languages with LDAP bindings

Go
Java
Python
Ruby

Server-side scripts

Stored procedures

yes

user defined functions

in Python

Triggers

yes

via Hawkular Alerting

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

cell division

Sharding

based on Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

selectable replication factor

based on Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency or Eventual Consistency depending on configuration

Eventual Consistency

based on Cassandra
Immediate Consistency

based on Cassandra

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

Atomic execution of specific operations

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

LDAP bind authentication

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