DBMS > Amazon Redshift vs. DuckDB vs. Firebase Realtime Database vs. SiteWhere

System Properties Comparison Amazon Redshift vs. DuckDB vs. Firebase Realtime Database vs. SiteWhere

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Editorial information provided by DB-Engines

Name

Description

Large scale data warehouse service for use with business intelligence tools

An embeddable, in-process, column-oriented SQL OLAP RDBMS

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

M2M integration platform for persisting/querying time series data

Primary database model

Relational DBMS

Document store

Time Series DBMS

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

Score	16.88
Rank	#35	Overall
	#22	Relational DBMS

Score	4.63
Rank	#69	Overall
	#37	Relational DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	0.06
Rank	#383	Overall
	#43	Time Series DBMS

Website

aws.amazon.com/redshift

duckdb.org

firebase.google.com/products/realtime-database

github.com/sitewhere/sitewhere

Technical documentation

docs.aws.amazon.com/redshift

duckdb.org/docs

firebase.google.com/docs/database

sitewhere1.sitewhere.io/index.html

Developer

Amazon (based on PostgreSQL)

Google

acquired by Google 2014

SiteWhere

Initial release

2012

2018

2012

2010

Current release

1.0.0, June 2024

License

Commercial or Open Source

commercial

Open Source

MIT License

commercial

Open Source

Common Public Attribution License Version 1.0

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

C++

Java

Server operating systems

hosted

server-less

hosted

Linux
OS X
Windows

Data scheme

yes

schema-free

predefined scheme

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

yes

APIs and other access methods

JDBC
ODBC

Arrow Database Connectivity (ADBC)
CLI Client
JDBC
ODBC

Android
iOS
JavaScript API
RESTful HTTP API

HTTP REST

Supported programming languages

All languages supporting JDBC/ODBC

C
C#

3rd party driver
C++
Crystal

3rd party driver
Go

3rd party driver
Java
Lisp

3rd party driver
Python
R
Ruby

3rd party driver
Rust
Swift
Zig

3rd party driver

Java
JavaScript
Objective-C

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

none

Sharding

based on HBase

Replication methods

Methods for redundantly storing data on multiple nodes

yes

none

selectable replication factor

based on HBase

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

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

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

Users with fine-grained authorization concept

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