DBMS > Fauna vs. Firebase Realtime Database vs. Firebird vs. Google BigQuery

System Properties Comparison Fauna vs. Firebase Realtime Database vs. Firebird vs. Google BigQuery

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Editorial information provided by DB-Engines

Name

Description

Fauna provides a web-native interface, with support for GraphQL and custom business logic that integrates seamlessly with the rest of the serverless ecosystem. The underlying globally distributed storage and compute platform is fast, consistent, and reliable, with a modern security infrastructure.

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

Firebird is an open source RDBMS forked from Borland's InterBase

Large scale data warehouse service with append-only tables

Primary database model

Document store
Graph DBMS
Relational DBMS
Time Series DBMS

Document store

Relational DBMS

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

Score	1.52
Rank	#153	Overall
	#26	Document stores
	#14	Graph DBMS
	#71	Relational DBMS
	#13	Time Series DBMS

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	20.82
Rank	#30	Overall
	#18	Relational DBMS

Score	60.38
Rank	#19	Overall
	#13	Relational DBMS

Website

fauna.com

firebase.google.com/products/realtime-database

www.firebirdsql.org

cloud.google.com/bigquery

Technical documentation

docs.fauna.com

firebase.google.com/docs/database

www.firebirdsql.org/en/reference-manuals

cloud.google.com/bigquery/docs

Developer

Fauna, Inc.

Google

acquired by Google 2014

Firebird Foundation

Google

Initial release

2014

2012

2000

As fork of Borland's InterBase

2010

Current release

5.0.0, January 2024

License

Commercial or Open Source

commercial

Open Source

Initial Developer's Public License

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

Scala

C and C++

Server operating systems

hosted

AIX
FreeBSD
HP-UX
Linux
OS X
server-less

Firebird Embedded Server
Solaris
Unix
Windows

hosted

Data scheme

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

yes

SQL

Support of SQL

yes

APIs and other access methods

RESTful HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET
C/C++ API
JDBC

Jaybird
ODBC
OLE DB

RESTful HTTP/JSON API

Supported programming languages

C#
Go
Java
JavaScript
Python
Ruby
Scala
Swift

Java
JavaScript
Objective-C

C
C#
C++
Delphi
Java
JavaScript

Node.js
Lua
Perl
PHP
Python
Ruby

.Net
Java
JavaScript
Objective-C
PHP
Python
Ruby

Server-side scripts

Stored procedures

user defined functions

limited functionality with using 'rules'

PSQL

user defined functions

in JavaScript

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning

consistent hashing

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

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

Transaction concepts

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

ACID

yes

ACID

Since BigQuery is designed for querying data

Concurrency

Support for concurrent manipulation of data

yes

Features a multi-generational MVCC architecture, readers do not block writers

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.

User concepts

Access control

Identity management, authentication, and access control

yes, based on authentication and database rules

Users with fine-grained authorization concept

Access privileges (owner, writer, reader) on dataset, table or view level

Google Cloud Identity & Access Management (IAM)

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