DBMS > Amazon Redshift vs. Firebase Realtime Database vs. RDFox

System Properties Comparison Amazon Redshift vs. Firebase Realtime Database 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

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

High performance knowledge graph and semantic reasoning engine

Primary database model

Relational DBMS

Document store

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	13.49
Rank	#39	Overall
	#6	Document stores

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

Website

aws.amazon.com/redshift

firebase.google.com/products/realtime-database

www.oxfordsemantic.tech

Technical documentation

docs.aws.amazon.com/redshift

firebase.google.com/docs/database

docs.oxfordsemantic.tech

Developer

Amazon (based on PostgreSQL)

Google

acquired by Google 2014

Oxford Semantic Technologies

Initial release

2012

2017

Current release

6.0, Septermber 2022

License

Commercial or Open Source

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

C++

Server operating systems

hosted

Linux
macOS
Windows

Data scheme

yes

schema-free

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

APIs and other access methods

JDBC
ODBC

Android
iOS
JavaScript API
RESTful HTTP API

RESTful HTTP API
SPARQL 1.1

Supported programming languages

All languages supporting JDBC/ODBC

Java
JavaScript
Objective-C

C
Java

Server-side scripts

Stored procedures

user defined functions

in Python

limited functionality with using 'rules'

Triggers

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

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

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

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

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

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

Roles, resources, and access types

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More resources

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