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

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

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

Open source search engine for searching in data from different sources, e.g. relational databases

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

Primary database model

Secondary database models

Relational 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	5.98
Rank	#56	Overall
	#5	Search engines

Score	0.11
Rank	#341	Overall
	#150	Relational DBMS

Website

firebase.google.com/products/firestore

postgis.net

www.snowflake.com

sphinxsearch.com

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

Technical documentation

firebase.google.com/docs/firestore

postgis.net/documentation

docs.snowflake.net/manuals/index.html

sphinxsearch.com/docs

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

Developer

Google

Snowflake Computing Inc.

Sphinx Technologies Inc.

Transaction Software GmbH

Initial release

2017

2005

2014

2001

1987

Current release

3.4.2, February 2024

3.5.1, February 2023

Transbase 8.3, 2022

License

Commercial or Open Source

commercial

Open Source

GPL v2.0

commercial

Open Source

GPL version 2, commercial licence available

commercial

free development license

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++

C and C++

Server operating systems

hosted

FreeBSD
Linux
NetBSD
OS X
Solaris
Windows

FreeBSD
Linux
macOS
Solaris
Windows

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

full-text index on all search fields

yes

SQL

Support of SQL

yes

SQL-like query language (SphinxQL)

yes

APIs and other access methods

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

CLI Client
JDBC
ODBC

Proprietary protocol

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

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

JavaScript (Node.js)
Python

C++

unofficial client library
Java
Perl

unofficial client library
PHP
Python
Ruby

unofficial client library

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

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

user defined functions

yes

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

Partitioning is done manually, search queries against distributed index is supported

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

yes

based on PostgreSQL

yes

none

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

The original contents of fields are not stored in the Sphinx index.

yes

In-memory capabilities

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

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

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