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DBMS > EsgynDB vs. Firebase Realtime Database vs. Google Cloud Bigtable vs. Google Cloud Firestore vs. SQL.JS

System Properties Comparison EsgynDB vs. Firebase Realtime Database vs. Google Cloud Bigtable vs. Google Cloud Firestore vs. SQL.JS

Editorial information provided by DB-Engines

Name

Description

Enterprise-class SQL-on-Hadoop solution, powered by Apache Trafodion

Cloud-hosted realtime document store. iOS, Android, and JavaScript clients share one Realtime Database instance and automatically receive updates with the newest data.

Google's NoSQL Big Data database service. It's the same database that powers many core Google services, including Search, Analytics, Maps, and Gmail.

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.

Port of SQLite to JavaScript

Primary database model

Relational DBMS

Key-value store
Wide column store

Relational DBMS

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

Score	0.25
Rank	#312	Overall
	#138	Relational DBMS

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	3.15
Rank	#95	Overall
	#14	Key-value stores
	#8	Wide column stores

Score	7.36
Rank	#53	Overall
	#9	Document stores

Score	0.63
Rank	#241	Overall
	#112	Relational DBMS

Website

firebase.google.com/products/realtime-database

cloud.google.com/bigtable

firebase.google.com/products/firestore

Technical documentation

firebase.google.com/docs/database

cloud.google.com/bigtable/docs

firebase.google.com/docs/firestore

sql.js.org/documentation/index.html

Developer

Esgyn

Google

acquired by Google 2014

Google

Google

Alon Zakai

enhancements implemented by others

Initial release

2015

2012

2015

2017

2012

License

Commercial or Open Source

commercial

commercial

commercial

commercial

Open Source

Cloud-based only

Only available as a cloud service

no

yes

yes

yes

no

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

C++, Java

JavaScript

Server operating systems

Linux

hosted

hosted

hosted

server-less, requires a JavaScript environment (browser, Node.js)

Data scheme

yes

schema-free

schema-free

schema-free

yes

Typing

predefined data types such as float or date

yes

yes

no

yes

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.

no

no

no

no

no

Secondary indexes

yes

yes

no

yes

SQL

Support of SQL

yes

no

no

no

yes

SQL-92 is not fully supported

APIs and other access methods

ADO.NET
JDBC
ODBC

Android
iOS
JavaScript API
RESTful HTTP API

gRPC (using protocol buffers) API
HappyBase (Python library)
HBase compatible API (Java)

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

JavaScript API

Supported programming languages

All languages supporting JDBC/ODBC/ADO.Net

Java
JavaScript
Objective-C

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

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

JavaScript

Server-side scripts

Stored procedures

Java Stored Procedures

limited functionality with using 'rules'

no

yes, Firebase Rules & Cloud Functions

no

Triggers

no

Callbacks are triggered when data changes

no

yes, with Cloud Functions

no

Partitioning methods

Methods for storing different data on different nodes

Sharding

Sharding

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication between multi datacenters

Internal replication in Colossus, and regional replication between two clusters in different zones

Multi-source replication

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

no

yes

Using Cloud Dataflow

no

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate consistency (for a single cluster), Eventual consistency (for two or more replicated clusters)

Immediate Consistency

none

Foreign keys

Referential integrity

yes

no

no

no

yes

Transaction concepts

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

ACID

yes

Atomic single-row operations

yes

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes

yes

yes

Durability

Support for making data persistent

yes

yes

yes

yes

no

except by serializing a db to a file

In-memory capabilities

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

no

no

yes

User concepts

Access control

fine grained access rights according to SQL-standard

yes, based on authentication and database rules

Access rights for users, groups and roles based on Google Cloud Identity and Access Management (IAM)

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

no

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More resources

DB-Engines blog posts

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

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

New kids on the block: database management systems implemented in JavaScript
1 December 2014, Matthias Gelbmann

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