DBMS > 4D vs. Amazon Redshift vs. MaxDB vs. Splice Machine

System Properties Comparison 4D vs. Amazon Redshift vs. MaxDB vs. Splice Machine

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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

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

Open-Source SQL RDBMS for Operational and Analytical use cases with native Machine Learning, powered by Hadoop and Spark

Primary database model

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	2.32
Rank	#112	Overall
	#55	Relational DBMS

Score	0.54
Rank	#250	Overall
	#114	Relational DBMS

Website

www.4d.com

aws.amazon.com/redshift

maxdb.sap.com

splicemachine.com

Technical documentation

developer.4d.com

docs.aws.amazon.com/redshift

maxdb.sap.com/documentation

splicemachine.com/how-it-works

Developer

4D, Inc

Amazon (based on PostgreSQL)

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

Splice Machine

Initial release

1984

2012

1984

2014

Current release

v20, April 2023

7.9.10.12, February 2024

3.1, March 2021

License

Commercial or Open Source

commercial

Limited community edition free

Open Source

AGPL 3.0, commercial license available

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++

Java

Server operating systems

OS X
Windows

hosted

AIX
HP-UX
Linux
Solaris
Windows

Linux
OS X
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

APIs and other access methods

ODBC
RESTful HTTP API

by using 4D Mobile
SOAP webservices

JDBC
ODBC

ADO.NET
JDBC
ODBC
WebDAV

JDBC
Native Spark Datasource
ODBC

Supported programming languages

4D proprietary IDE
PHP

All languages supporting JDBC/ODBC

.Net
C#
Java
Perl
PHP
Python

C#
C++
Java
JavaScript (Node.js)
Python
R
Scala

Server-side scripts

Stored procedures

yes

user defined functions

in Python

yes

Java

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

none

Shared Nothhing Auto-Sharding, Columnar Partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

Source-replica replication

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Yes, via Full Spark Integration

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

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Access rights for users, groups and roles according to SQL-standard

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