DBMS > Google Cloud Firestore vs. Ingres vs. MySQL vs. RocksDB vs. Snowflake

System Properties Comparison Google Cloud Firestore vs. Ingres vs. MySQL vs. RocksDB vs. Snowflake

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.

Well established RDBMS

Widely used open source RDBMS

Embeddable persistent key-value store optimized for fast storage (flash and RAM)

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

Primary database model

Document store

Relational DBMS

Key/Value like access via memcached API

Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	3.80
Rank	#82	Overall
	#44	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	3.41
Rank	#86	Overall
	#11	Key-value stores

Score	130.36
Rank	#8	Overall
	#5	Relational DBMS

Website

firebase.google.com/products/firestore

www.actian.com/databases/ingres

www.mysql.com

rocksdb.org

www.snowflake.com

Technical documentation

firebase.google.com/docs/firestore

docs.actian.com/ingres

dev.mysql.com/doc

github.com/facebook/rocksdb/wiki

docs.snowflake.net/manuals/index.html

Developer

Google

Actian Corporation

Oracle

since 2010, originally MySQL AB, then Sun

Facebook, Inc.

Snowflake Computing Inc.

Initial release

2017

1974

originally developed at University Berkely in early 1970s

1995

2013

2014

Current release

11.2, May 2022

8.4.0, April 2024

9.2.1, May 2024

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

BSD

commercial

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

C and C++

C++

Server operating systems

hosted

AIX
HP Open VMS
HP-UX
Linux
Solaris
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux

hosted

Data scheme

schema-free

yes

schema-free

yes

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

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.

but tools for importing/exporting data from/to XML-files available

yes

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

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

.NET Client API
JDBC
ODBC
proprietary protocol (OpenAPI)

ADO.NET
JDBC
ODBC
Proprietary native API

C++ API
Java API

CLI Client
JDBC
ODBC

Supported programming languages

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

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

C
C++
Go
Java
Perl
Python
Ruby

JavaScript (Node.js)
Python

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

proprietary syntax

user defined functions

Triggers

yes, with Cloud Functions

yes

similar concept for controling cloud resources

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

Ingres Star to access multiple databases simultaneously

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

yes

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Ingres Replicator

Multi-source replication
Source-replica replication

yes

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

not for MyISAM storage engine

yes

Transaction concepts

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

yes

ACID

not for MyISAM storage engine

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC

yes

table locks or row locks depending on storage engine

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

Users with fine-grained authorization concept

no user groups or roles

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

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