DBMS > Google Cloud Firestore vs. HyperSQL vs. mSQL vs. PostgreSQL vs. Sequoiadb

System Properties Comparison Google Cloud Firestore vs. HyperSQL vs. mSQL vs. PostgreSQL vs. Sequoiadb

Editorial information provided by DB-Engines

Name

Description

Cloud Firestore is an auto-scaling document database for storing, syncing, and querying data for mobile and web apps. It offers seamless integration with other Firebase and Google Cloud Platform products.

Multithreaded, transactional RDBMS written in Java

also known as HSQLDB

mSQL (Mini SQL) is a simple and lightweight RDBMS

Widely used open source RDBMS

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

NewSQL database with distributed OLTP and SQL

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

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	7.85
Rank	#51	Overall
	#8	Document stores

Score	3.49
Rank	#87	Overall
	#47	Relational DBMS

Score	1.27
Rank	#167	Overall
	#77	Relational DBMS

Score	645.54
Rank	#4	Overall
	#4	Relational DBMS

Score	0.45
Rank	#261	Overall
	#41	Document stores
	#122	Relational DBMS

Website

firebase.google.com/products/firestore

hsqldb.org

hughestech.com.au/products/msql

www.postgresql.org

www.sequoiadb.com

Technical documentation

firebase.google.com/docs/firestore

hsqldb.org/web/hsqlDocsFrame.html

www.postgresql.org/docs

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

Developer

Google

Hughes Technologies

PostgreSQL Global Development Group

www.postgresql.org/developer

Sequoiadb Ltd.

Initial release

2017

2001

1994

1989

1989: Postgres, 1996: PostgreSQL

2013

Current release

2.7.2, June 2023

4.4, October 2021

16.3, May 2024

License

Commercial or Open Source

commercial

Open Source

based on BSD license

commercial

free licenses can be provided

Open Source

BSD

Open Source

Server: AGPL; Client: Apache V2

Cloud-based only

Only available as a cloud service

yes

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Implementation language

Java

C++

Server operating systems

hosted

All OS with a Java VM

Embedded (into Java applications) and Client-Server operating modes

AIX
HP-UX
Linux
OS X
Solaris SPARC/x86
Windows

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

Linux

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

oid, date, timestamp, binary, regex

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

A subset of ANSI SQL is implemented

no subqueries, aggregate functions, views, foreign keys, triggers

yes

standard with numerous extensions

SQL-like query language

APIs and other access methods

Android
gRPC (using protocol buffers) API
iOS
JavaScript API
RESTful HTTP API

HTTP API

JDBC via HTTP
JDBC
ODBC

JDBC
ODBC

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

proprietary protocol using JSON

Supported programming languages

Go
Java
JavaScript
JavaScript (Node.js)
Objective-C
Python

All languages supporting JDBC/ODBC
Java

C
C++
Delphi
Java
Perl
PHP
Tcl

.Net
C
C++
Delphi
Java

JDBC
JavaScript (Node.js)
Perl
PHP
Python
Tcl

.Net
C++
Java
PHP
Python

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

Java, SQL

user defined functions

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

JavaScript

Triggers

yes, with Cloud Functions

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

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

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

none

Source-replica replication

other methods possible by using 3rd party extensions

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

none

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

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

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

fine grained access rights according to SQL-standard

simple password-based access control

More information provided by the system vendor

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and for displaying vendor-provided information such as key customers, competitive advantages and market metrics.

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