DBMS > Firebase Realtime Database vs. HBase vs. RethinkDB vs. Snowflake vs. WakandaDB

System Properties Comparison Firebase Realtime Database vs. HBase vs. RethinkDB vs. Snowflake vs. WakandaDB

Editorial information provided by DB-Engines

Name

Description

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

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

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

Cloud-based data warehousing service for structured and semi-structured data

WakandaDB is embedded in a server that provides a REST API and a server-side javascript engine to access data

Primary database model

Secondary database models

Spatial DBMS

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	30.50
Rank	#26	Overall
	#2	Wide column stores

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	121.33
Rank	#9	Overall
	#6	Relational DBMS

Score	0.03
Rank	#364	Overall
	#17	Object oriented DBMS

Website

firebase.google.com/products/realtime-database

Technical documentation

firebase.google.com/docs/database

hbase.apache.org/book.html

rethinkdb.com/docs

docs.snowflake.net/manuals/index.html

wakanda.github.io/doc

Developer

Google

acquired by Google 2014

Apache Software Foundation

Apache top-level project, originally developed by Powerset

The Linux Foundation

since July 2017

Snowflake Computing Inc.

Wakanda SAS

Initial release

2012

2008

2009

2014

2012

Current release

2.3.4, January 2021

2.4.1, August 2020

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

Apache version 2

Open Source

Apache Version 2

commercial

Open Source

AGPLv3, extended 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

Java

C++

C++, JavaScript

Server operating systems

hosted

Linux
Unix
Windows

using Cygwin

Linux
OS X
Windows

hosted

Linux
OS X
Windows

Data scheme

schema-free

schema-free, schema definition possible

schema-free

yes

support of semi-structured data formats (JSON, XML, Avro)

yes

Typing

predefined data types such as float or date

yes

options to bring your own types, AVRO

yes

string, binary, float, bool, date, geometry

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.

yes

Secondary indexes

yes

SQL

Support of SQL

yes

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

Java API
RESTful HTTP API
Thrift

CLI Client
JDBC
ODBC

RESTful HTTP API

Supported programming languages

Java
JavaScript
Objective-C

C
C#
C++
Groovy
Java
PHP
Python
Scala

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

JavaScript (Node.js)
Python

JavaScript

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

Coprocessors in Java

user defined functions

yes

Triggers

Callbacks are triggered when data changes

yes

Client-side triggers through changefeeds

similar concept for controling cloud resources

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

range based

yes

none

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Source-replica replication

yes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Eventual Consistency

if the client is offline
Immediate Consistency

if the client is online

Immediate Consistency or Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

Single row ACID (across millions of columns)

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

yes, based on authentication and database rules

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

yes

users and table-level permissions

Users with fine-grained authorization concept, user roles and pluggable authentication

yes

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