DBMS > Amazon Redshift vs. Firebase Realtime Database vs. JaguarDB vs. Netezza

System Properties Comparison Amazon Redshift vs. Firebase Realtime Database vs. JaguarDB vs. Netezza

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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.

Performant, highly scalable DBMS for AI and IoT applications

Data warehouse and analytics appliance part of IBM PureSystems

Primary database model

Relational DBMS

Document store

Key-value store
Vector DBMS

Relational DBMS

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

Score	17.94
Rank	#34	Overall
	#21	Relational DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	0.00
Rank	#383	Overall
	#60	Key-value stores
	#13	Vector DBMS

Score	9.06
Rank	#46	Overall
	#29	Relational DBMS

Website

aws.amazon.com/redshift

firebase.google.com/products/realtime-database

www.jaguardb.com

www.ibm.com/products/netezza

Technical documentation

docs.aws.amazon.com/redshift

firebase.google.com/docs/database

www.jaguardb.com/support.html

Developer

Amazon (based on PostgreSQL)

Google

acquired by Google 2014

DataJaguar, Inc.

IBM

Initial release

2012

2015

2000

Current release

3.3 July 2023

License

Commercial or Open Source

commercial

Open Source

GPL V3.0

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++

the server part. Clients available in other languages

Server operating systems

hosted

Linux

included in appliance

Data scheme

yes

schema-free

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.

Secondary indexes

restricted

yes

SQL

Support of SQL

yes

does not fully support an SQL-standard

A subset of ANSI SQL is implemented

but no views, foreign keys, triggers

yes

APIs and other access methods

JDBC
ODBC

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC

JDBC
ODBC
OLE DB

Supported programming languages

All languages supporting JDBC/ODBC

Java
JavaScript
Objective-C

C
C++
Go
Java
JavaScript (Node.js)
PHP
Python
Ruby
Scala

C
C++
Fortran
Java
Lua
Perl
Python
R

Server-side scripts

Stored procedures

user defined functions

in Python

limited functionality with using 'rules'

yes

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

Multi-source replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

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

Eventual 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

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

rights management via user accounts

Users with fine-grained authorization concept

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