DBMS > DataFS vs. Google Cloud Firestore vs. Quasardb

System Properties Comparison DataFS vs. Google Cloud Firestore vs. Quasardb

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Editorial information provided by DB-Engines

Name

Description

All data is stored inside objects which are linked by so-called link attributes. Objects consist of classes which can be extended and de-extended at runtime. Graphs can be defined with a struct.

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.

Distributed, high-performance timeseries database

Primary database model

Object oriented DBMS

Document store

Time Series DBMS

Secondary database models

Graph DBMS

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

Score	0.07
Rank	#362	Overall
	#17	Object oriented DBMS

Score	8.96
Rank	#48	Overall
	#8	Document stores

Score	0.19
Rank	#327	Overall
	#30	Time Series DBMS

Website

newdatabase.com

firebase.google.com/products/firestore

quasar.ai

Technical documentation

dev.mobiland.com/Overview.xsp

firebase.google.com/docs/firestore

doc.quasar.ai/master

Developer

Mobiland AG

Google

quasardb

Initial release

2018

2017

2009

Current release

1.1.263, October 2022

3.14.1, January 2024

License

Commercial or Open Source

commercial

Free community edition, Non-profit organizations and non-commercial usage are eligible for free licenses

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++

Server operating systems

Windows

hosted

BSD
Linux
OS X
Windows

Data scheme

Classes, Structs, and Lists are written in proprietary DataTypeDefinitionLanguage (.dtdl) and Objects consisting of those are written in proprietary DataAccessDefinitionLanguage (.dadl)

schema-free

Typing

predefined data types such as float or date

yes

integer and binary

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.

Secondary indexes

yes

with tags

SQL

Support of SQL

SQL-like query language

APIs and other access methods

.NET Client API
Proprietary client DLL
WinRT client

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

HTTP API

Supported programming languages

.Net
C
C#
C++
VB.Net

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

.Net
C
C#
C++
Go
Java
JavaScript (Node.js)
PHP
Python
R

Server-side scripts

Stored procedures

yes, Firebase Rules & Cloud Functions

Triggers

no, except callback-events from server when changes happened

yes, with Cloud Functions

Partitioning methods

Methods for storing different data on different nodes

Proprietary Sharding system

Sharding

consistent hashing

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication

Source-replica replication with selectable replication factor

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

by using LevelDB

In-memory capabilities

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

yes

Transient mode

User concepts

Access control

Windows-Profile

Access rights for users, groups and roles based on Google Cloud Identity and Access Management. Security Rules for 3rd party authentication using Firebase Auth.

Cryptographically strong user authentication and audit trail

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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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