DBMS > Apache HBase vs. Firebase Realtime Database

System Properties Comparison Apache HBase vs. Firebase Realtime Database

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Editorial information provided by DB-Engines

Name

Description

Wide-column store based on Apache Hadoop and on concepts of BigTable

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

Primary database model

Wide column store

Document store

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

Score	22.62
Rank	#27	Overall
	#3	Wide column stores

Score	13.43
Rank	#39	Overall
	#6	Document stores

Website

hbase.apache.org

firebase.google.com/products/realtime-database

Technical documentation

hbase.apache.org/book.html

firebase.google.com/docs/database

Developer

Apache Software Foundation

Apache top-level project, originally developed by Powerset

Google

acquired by Google 2014

Initial release

2008

2012

Current release

2.3.4, January 2021

License

Commercial or Open Source

Open Source

Apache version 2

commercial

Cloud-based only

Only available as a cloud service

yes

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Database as a Service

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Implementation language

Java

Server operating systems

Linux
Unix
Windows

using Cygwin

hosted

Data scheme

schema-free, schema definition possible

schema-free

Typing

predefined data types such as float or date

options to bring your own types, AVRO

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.

Secondary indexes

yes

SQL

Support of SQL

APIs and other access methods

Java API
RESTful HTTP API
Thrift

Android
iOS
JavaScript API
RESTful HTTP API

Supported programming languages

C
C#
C++
Groovy
Java
PHP
Python
Scala

Java
JavaScript
Objective-C

Server-side scripts

Stored procedures

yes

Coprocessors in Java

limited functionality with using 'rules'

Triggers

yes

Callbacks are triggered when data changes

Partitioning methods

Methods for storing different data on different nodes

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency or Eventual Consistency

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Foreign keys

Referential integrity

Transaction concepts

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

Single row ACID (across millions of columns)

yes

Concurrency

Support for concurrent manipulation of data

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 Control Lists (ACL) for RBAC, integration with Apache Ranger for RBAC & ABAC

yes, based on authentication and database rules

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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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