DBMS > Amazon Redshift vs. Apache Derby vs. RDFox

System Properties Comparison Amazon Redshift vs. Apache Derby vs. RDFox

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

High performance knowledge graph and semantic reasoning engine

Primary database model

Relational DBMS

Graph DBMS
RDF store

Secondary database models

Relational DBMS

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

Score	14.57
Rank	#37	Overall
	#22	Relational DBMS

Score	3.42
Rank	#76	Overall
	#41	Relational DBMS

Score	0.26
Rank	#291	Overall
	#23	Graph DBMS
	#12	RDF stores

Website

aws.amazon.com/redshift

db.apache.org/derby

www.oxfordsemantic.tech

Technical documentation

docs.aws.amazon.com/redshift

db.apache.org/derby/manuals/index.html

docs.oxfordsemantic.tech

Developer

Amazon (based on PostgreSQL)

Apache Software Foundation

Oxford Semantic Technologies

Initial release

2012

1997

2017

Current release

10.17.1.0, November 2023

6.0, Septermber 2022

License

Commercial or Open Source

commercial

Open Source

Apache version 2

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

Java

C++

Server operating systems

hosted

All OS with a Java VM

Linux
macOS
Windows

Data scheme

yes

RDF schemas

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

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

yes

APIs and other access methods

JDBC
ODBC

JDBC

RESTful HTTP API
SPARQL 1.1

Supported programming languages

All languages supporting JDBC/ODBC

Java

C
Java

Server-side scripts

Stored procedures

user defined functions

in Python

Java Stored Procedures

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

yes

Source-replica replication

replication via a shared file system

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in stand-alone mode, Eventual Consistency in replicated setups

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

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

Roles, resources, and access types

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
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7 February 2017, Matthias Gelbmann

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2 October 2015, Paul Andlinger

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