DBMS > Google Cloud Firestore vs. PostGIS vs. Snowflake vs. Transbase vs. Vitess

System Properties Comparison Google Cloud Firestore vs. PostGIS vs. Snowflake vs. Transbase vs. Vitess

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.

Spatial extension of PostgreSQL

Cloud-based data warehousing service for structured and semi-structured data

A resource-optimized, high-performance, universally applicable RDBMS

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Document store

Spatial DBMS

Relational DBMS

Secondary database models

Relational DBMS

Document store
Spatial DBMS

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

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	22.69
Rank	#29	Overall
	#1	Spatial DBMS

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

firebase.google.com/products/firestore

postgis.net

www.snowflake.com

www.transaction.de/en/products/transbase.html

vitess.io

Technical documentation

firebase.google.com/docs/firestore

postgis.net/documentation

docs.snowflake.net/manuals/index.html

www.transaction.de/en/products/transbase/features.html

vitess.io/docs

Developer

Google

Snowflake Computing Inc.

Transaction Software GmbH

The Linux Foundation, PlanetScale

Initial release

2017

2005

2014

1987

2013

Current release

3.4.2, February 2024

Transbase 8.3, 2022

15.0.2, December 2022

License

Commercial or Open Source

commercial

Open Source

GPL v2.0

commercial

free development license

Open Source

Apache Version 2.0, commercial licenses available

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 and C++

Server operating systems

hosted

FreeBSD
Linux
macOS
Solaris
Windows

Docker
Linux
macOS

Data scheme

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

APIs and other access methods

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

CLI Client
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

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

JavaScript (Node.js)
Python

C
C#
C++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

user defined functions

yes

proprietary syntax

Triggers

yes, with Cloud Functions

yes

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

yes

based on PostgreSQL

yes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

based on PostgreSQL

yes

Source-replica replication

Multi-source replication
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

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

yes

ACID

yes

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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.

yes

based on PostgreSQL

Users with fine-grained authorization concept, user roles and pluggable authentication

fine grained access rights according to SQL-standard

Users with fine-grained authorization concept

no user groups or roles

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