DBMS > Google Cloud Firestore vs. MySQL vs. OrigoDB vs. TimesTen

System Properties Comparison Google Cloud Firestore vs. MySQL vs. OrigoDB vs. TimesTen

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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.

Widely used open source RDBMS

A fully ACID in-memory object graph database

In-Memory RDBMS compatible to Oracle

Primary database model

Document store

Relational DBMS

Key/Value like access via memcached API

Document store
Object oriented DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	8.96
Rank	#48	Overall
	#8	Document stores

Score	1087.72
Rank	#2	Overall
	#2	Relational DBMS

Score	0.03
Rank	#378	Overall
	#51	Document stores
	#18	Object oriented DBMS

Score	1.35
Rank	#165	Overall
	#75	Relational DBMS

Website

firebase.google.com/products/firestore

www.mysql.com

origodb.com

www.oracle.com/database/technologies/related/timesten.html

Technical documentation

firebase.google.com/docs/firestore

dev.mysql.com/doc

origodb.com/docs

docs.oracle.com/database/timesten-18.1

Developer

Google

Oracle

since 2010, originally MySQL AB, then Sun

Robert Friberg et al

Oracle, TimesTen Performance Software, HP

originally founded in HP Labs it was acquired by Oracle in 2005

Initial release

2017

1995

2009

under the name LiveDB

1998

Current release

8.3.0, January 2024

11 Release 2 (11.2.2.8.0)

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

commercial

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C and C++

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

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

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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

can be achieved using .NET

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

ADO.NET
JDBC
ODBC
Proprietary native API

.NET Client API
HTTP API
LINQ

JDBC
ODBC
ODP.NET
Oracle Call Interface (OCI)

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

.Net

C
C++
Java
PL/SQL

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

proprietary syntax

yes

PL/SQL

Triggers

yes, with Cloud Functions

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

client side managed; servers are not synchronized

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Multi-source replication
Source-replica replication

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

Immediate Consistency or Eventual Consistency depending on configuration

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

depending on model

yes

Transaction concepts

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

yes

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

by means of logfiles and checkpoints

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.

Users with fine-grained authorization concept

no user groups or roles

Role based authorization

fine grained access rights according to SQL-standard

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