DBMS > Google Cloud Firestore vs. Oracle NoSQL vs. OrigoDB vs. RocksDB

System Properties Comparison Google Cloud Firestore vs. Oracle NoSQL vs. OrigoDB vs. RocksDB

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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.

A multi-model, scalable, distributed NoSQL database, designed to provide highly reliable, flexible, and available data management across a configurable set of storage nodes

A fully ACID in-memory object graph database

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

Primary database model

Document store

Document store
Key-value store
Relational DBMS

Document store
Object oriented DBMS

Key-value store

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

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	3.05
Rank	#97	Overall
	#17	Document stores
	#16	Key-value stores
	#50	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

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

Website

firebase.google.com/products/firestore

www.oracle.com/database/nosql/technologies/nosql

origodb.com

rocksdb.org

Technical documentation

firebase.google.com/docs/firestore

docs.oracle.com/en/database/other-databases/nosql-database/index.html

origodb.com/docs

github.com/facebook/rocksdb/wiki

Developer

Google

Oracle

Robert Friberg et al

Facebook, Inc.

Initial release

2017

2011

2009

under the name LiveDB

2013

Current release

24.1, May 2024

9.2.1, May 2024

License

Commercial or Open Source

commercial

Open Source

Proprietary for Enterprise Edition (Oracle Database EE license has Oracle NoSQL database EE covered: details)

Open Source

BSD

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

Java

C++

Server operating systems

hosted

Linux
Solaris SPARC/x86

Linux
Windows

Linux

Data scheme

schema-free

Support Fixed schema and Schema-less deployment with the ability to interoperate between them.

yes

schema-free

Typing

predefined data types such as float or date

yes

optional

User defined using .NET types and collections

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.

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

SQL-like DML and DDL statements

APIs and other access methods

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

RESTful HTTP API

.NET Client API
HTTP API
LINQ

C++ API
Java API

Supported programming languages

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

C
C#
Go
Java
JavaScript (Node.js)
Python

.Net

C
C++
Go
Java
Perl
Python
Ruby

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

yes

Triggers

yes, with Cloud Functions

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning

client side managed; servers are not synchronized

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Electable source-replica replication per shard. Support distributed global deployment with Multi-region table feature

Source-replica replication

yes

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

with Hadoop integration

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency
Immediate Consistency

depending on configuration

Foreign keys

Referential integrity

depending on model

Transaction concepts

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

yes

configurable

ACID within a storage node (=shard)

ACID

yes

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

yes

In-memory capabilities

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

yes

off heap cache

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.

Access rights for users and roles

Role based authorization

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