DBMS > 4D vs. Amazon Redshift vs. IBM Db2 Event Store vs. MaxDB

System Properties Comparison 4D vs. Amazon Redshift vs. IBM Db2 Event Store vs. MaxDB

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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

Distributed Event Store optimized for Internet of Things use cases

A robust and reliable RDBMS optimized to run all major SAP solutions

Primary database model

Relational DBMS

Event Store
Time Series DBMS

Relational 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	0.19
Rank	#323	Overall
	#2	Event Stores
	#28	Time Series DBMS

Score	2.32
Rank	#112	Overall
	#55	Relational DBMS

Website

www.4d.com

aws.amazon.com/redshift

www.ibm.com/products/db2-event-store

maxdb.sap.com

Technical documentation

developer.4d.com

docs.aws.amazon.com/redshift

www.ibm.com/docs/en/db2-event-store

maxdb.sap.com/documentation

Developer

4D, Inc

Amazon (based on PostgreSQL)

IBM

SAP, acquired from Software AG (Adabas-D) in 1997

Initial release

1984

2012

2017

1984

Current release

v20, April 2023

2.0

7.9.10.12, February 2024

License

Commercial or Open Source

commercial

free developer edition available

commercial

Limited community edition free

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

C and C++

C++

Server operating systems

OS X
Windows

hosted

Linux

Linux, macOS, Windows for the developer addition

AIX
HP-UX
Linux
Solaris
Windows

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

through the embedded Spark runtime

yes

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC

ADO.NET
DB2 Connect
JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC
WebDAV

Supported programming languages

4D proprietary IDE
PHP

All languages supporting JDBC/ODBC

C
C#
C++
Cobol
Delphi
Fortran
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
R
Ruby
Scala
Visual Basic

.Net
C#
Java
Perl
PHP
Python

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

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Active-active shard replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

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

No - written data is immutable

yes

Durability

Support for making data persistent

yes

Yes - Synchronous writes to local disk combined with replication and asynchronous writes in parquet format to permanent shared storage

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

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