DBMS > Firebase Realtime Database vs. PostgreSQL vs. Sequoiadb vs. XTDB

System Properties Comparison Firebase Realtime Database vs. PostgreSQL vs. Sequoiadb vs. XTDB

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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.

Widely used open source RDBMS

Developed as objectoriented DBMS (Postgres), gradually enhanced with 'standards' like SQL

NewSQL database with distributed OLTP and SQL

A general purpose database with bitemporal SQL and Datalog and graph queries

Primary database model

Document store

Relational DBMS

with object oriented extensions, e.g.: user defined types/functions and inheritance. Handling of key/value pairs with hstore module.

Document store
Relational DBMS

Document store

Secondary database models

Document store
Graph DBMS

with Apache Age
Spatial DBMS
Vector DBMS

with pgvector extension

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

Score	13.43
Rank	#39	Overall
	#6	Document stores

Score	674.32
Rank	#4	Overall
	#4	Relational DBMS

Score	0.32
Rank	#272	Overall
	#43	Document stores
	#125	Relational DBMS

Score	0.20
Rank	#314	Overall
	#46	Document stores

Website

firebase.google.com/products/realtime-database

www.postgresql.org

www.sequoiadb.com

github.com/xtdb/xtdb
www.xtdb.com

Technical documentation

firebase.google.com/docs/database

www.postgresql.org/docs

www.sequoiadb.com/en/index.php?m=Files&a=index

www.xtdb.com/docs

Developer

Google

acquired by Google 2014

PostgreSQL Global Development Group

www.postgresql.org/developer

Sequoiadb Ltd.

Juxt Ltd.

Initial release

2012

1989

1989: Postgres, 1996: PostgreSQL

2013

2019

Current release

16.4, August 2024

1.19, September 2021

License

Commercial or Open Source

commercial

Open Source

BSD

Open Source

Server: AGPL; Client: Apache V2

Open Source

MIT License

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C++

Clojure

Server operating systems

hosted

FreeBSD
HP-UX
Linux
NetBSD
OpenBSD
OS X
Solaris
Unix
Windows

Linux

All OS with a Java 8 (and higher) VM
Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

yes, extensible-data-notation format

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

specific XML-type available, but no XML query functionality.

Secondary indexes

yes

SQL

Support of SQL

yes

standard with numerous extensions

SQL-like query language

limited SQL, making use of Apache Calcite

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

proprietary protocol using JSON

HTTP REST
JDBC

Supported programming languages

Java
JavaScript
Objective-C

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C++
Java
PHP
Python

Clojure
Java

Server-side scripts

Stored procedures

limited functionality with using 'rules'

user defined functions

realized in proprietary language PL/pgSQL or with common languages like Perl, Python, Tcl etc.

JavaScript

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

partitioning by range, list and (since PostgreSQL 11) by hash

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

other methods possible by using 3rd party extensions

Source-replica replication

yes, each node contains all data

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

Document is locked during a transaction

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

yes, flexibel persistency by using storage technologies like Apache Kafka, RocksDB or LMDB

In-memory capabilities

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

User concepts

Access control

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

simple password-based access control

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