DBMS > Google Cloud Firestore vs. RethinkDB vs. Stardog vs. STSdb

System Properties Comparison Google Cloud Firestore vs. RethinkDB vs. Stardog vs. STSdb

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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.

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Enterprise Knowledge Graph platform and graph DBMS with high availability, high performance reasoning, and virtualization

Key-Value Store with special method for indexing

optimized for high performance using a special indexing method

Primary database model

Document store

Graph DBMS
RDF store

Key-value store

Secondary database models

Spatial DBMS

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

Score	7.85
Rank	#51	Overall
	#8	Document stores

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	2.02
Rank	#123	Overall
	#11	Graph DBMS
	#6	RDF stores

Score	0.04
Rank	#360	Overall
	#52	Key-value stores

Website

firebase.google.com/products/firestore

rethinkdb.com

www.stardog.com

github.com/STSSoft/STSdb4

Technical documentation

firebase.google.com/docs/firestore

rethinkdb.com/docs

docs.stardog.com

Developer

Google

The Linux Foundation

since July 2017

Stardog-Union

STS Soft SC

Initial release

2017

2009

2010

2011

Current release

2.4.1, August 2020

7.3.0, May 2020

4.0.8, September 2015

License

Commercial or Open Source

commercial

Open Source

Apache Version 2

commercial

60-day fully-featured trial license; 1-year fully-featured non-commercial use license for academics/students

Open Source

GPLv2, commercial license 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++

Java

Server operating systems

hosted

Linux
OS X
Windows

Linux
macOS
Windows

Windows

Data scheme

schema-free

schema-free and OWL/RDFS-schema support

yes

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

yes

primitive types and user defined types (classes)

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.

Import/export of XML data possible

Secondary indexes

yes

supports real-time indexing in full-text and geospatial

SQL

Support of SQL

Yes, compatible with all major SQL variants through dedicated BI/SQL Server

APIs and other access methods

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

GraphQL query language
HTTP API
Jena RDF API
OWL
RDF4J API
Sesame REST HTTP Protocol
SNARL
SPARQL
Spring Data
Stardog Studio
TinkerPop 3

.NET Client API

Supported programming languages

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

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

.Net
Clojure
Groovy
Java
JavaScript
Python
Ruby

C#
Java

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

user defined functions and aggregates, HTTP Server extensions in Java

Triggers

yes, with Cloud Functions

Client-side triggers through changefeeds

yes

via event handlers

Partitioning methods

Methods for storing different data on different nodes

Sharding

range based

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication

Multi-source replication in HA-Cluster

none

MapReduce

Offers an API for user-defined Map/Reduce methods

Using Cloud Dataflow

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Immediate Consistency in HA-Cluster

Foreign keys

Referential integrity

yes

relationships in graphs

Transaction concepts

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

yes

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

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.

yes

users and table-level permissions

Access rights for users and roles

More information provided by the system vendor

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More resources

DB-Engines blog posts

Cloud-based DBMS's popularity grows at high rates
12 December 2019, Paul Andlinger

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Recent citations in the news

Realtime vs Cloud Firestore: Which Firebase Database to go?
8 March 2024, Appinventiv

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1 March 2024, Forbes

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10 May 2023, TechCrunch

Google's Cloud Firestore is now generally available
31 January 2019, ZDNet

Firestore and Python | NoSQL on Google Cloud
7 August 2020, Towards Data Science

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