DBMS > Firebase Realtime Database vs. InterSystems IRIS vs. NSDb

System Properties Comparison Firebase Realtime Database vs. InterSystems IRIS vs. NSDb

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Editorial information provided by DB-Engines

Name

Description

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

A containerised multi-model DBMS, interoperability and analytics data platform with wide capabilities for vertical and horizontal scalability

Scalable, High-performance Time Series DBMS designed for Real-time Analytics on top of Kubernetes

Primary database model

Document store

Document store
Key-value store
Object oriented DBMS
Relational DBMS

Time Series DBMS

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

Score	13.15
Rank	#39	Overall
	#6	Document stores

Score	2.20
Rank	#110	Overall
	#20	Document stores
	#17	Key-value stores
	#1	Object oriented DBMS
	#54	Relational DBMS

Score	0.00
Rank	#382	Overall
	#41	Time Series DBMS

Website

firebase.google.com/products/realtime-database

www.intersystems.com/products/intersystems-iris

nsdb.io

Technical documentation

firebase.google.com/docs/database

docs.intersystems.com/irislatest/csp/docbook/DocBook.UI.Page.cls

nsdb.io/Architecture

Developer

Google

acquired by Google 2014

InterSystems

Initial release

2012

2018

2017

Current release

2023.3, June 2023

License

Commercial or Open Source

commercial

Open Source

Apache Version 2.0

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

Java, Scala

Server operating systems

hosted

AIX
Linux
macOS
Ubuntu
Windows

Linux
macOS

Data scheme

schema-free

depending on used data model

Typing

predefined data types such as float or date

yes

yes: int, bigint, decimal, string

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

all fields are automatically indexed

SQL

Support of SQL

yes

SQL-like query language

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

JDBC
ODBC
RESTful HTTP API

gRPC
HTTP REST
WebSocket

Supported programming languages

Java
JavaScript
Objective-C

.Net
C++
Java
JavaScript (Node.js)
Python

Java
Scala

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency

Eventual Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Using Apache Lucene

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

yes, based on authentication and database rules

yes

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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