DBMS > Firebase Realtime Database vs. Google Cloud Bigtable vs. H2GIS vs. Riak TS vs. WakandaDB

System Properties Comparison Firebase Realtime Database vs. Google Cloud Bigtable vs. H2GIS vs. Riak TS 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.

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

Spatial extension of H2

Riak TS is a distributed NoSQL database optimized for time series data and based on Riak KV

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

Primary database model

Document store

Key-value store
Wide column store

Spatial DBMS

Time Series DBMS

Object oriented DBMS

Secondary database models

Relational DBMS

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

Score	13.64
Rank	#39	Overall
	#6	Document stores

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

Score	0.08
Rank	#368	Overall
	#7	Spatial DBMS

Score	0.28
Rank	#307	Overall
	#27	Time Series DBMS

Score	0.10
Rank	#356	Overall
	#16	Object oriented DBMS

Website

firebase.google.com/products/realtime-database

cloud.google.com/bigtable

www.h2gis.org

wakanda.github.io

Technical documentation

firebase.google.com/docs/database

cloud.google.com/bigtable/docs

www.h2gis.org/docs/home

www.tiot.jp/riak-docs/riak/ts/latest

wakanda.github.io/doc

Developer

Google

acquired by Google 2014

Google

CNRS

Open Source, formerly Basho Technologies

Wakanda SAS

Initial release

2012

2015

2013

2015

2012

Current release

3.0.0, September 2022

2.7.0 (April 29, 2019), April 2019

License

Commercial or Open Source

commercial

Open Source

LGPL 3.0

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

Erlang

C++, JavaScript

Server operating systems

hosted

Linux
OS X

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

yes

Typing

predefined data types such as float or date

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

restricted

SQL

Support of SQL

yes

yes, limited

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

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

HTTP API
Native Erlang Interface

RESTful HTTP API

Supported programming languages

Java
JavaScript
Objective-C

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

Java

unofficial client library
C#
C++

unofficial client library
Clojure

unofficial client library
Dart

unofficial client library
Erlang
Go

unofficial client library
Groovy

unofficial client library
Haskell

unofficial client library
Java
JavaScript

unofficial client library
Lisp

unofficial client library
Perl

unofficial client library
PHP
Python
Ruby
Scala

unofficial client library
Smalltalk

unofficial client library

JavaScript

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

based on H2

Erlang

yes

Triggers

Callbacks are triggered when data changes

yes

pre-commit hooks and post-commit hooks

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

Sharding

none

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

based on H2

selectable replication factor

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

Immediate Consistency

Eventual Consistency

Immediate Consistency

Foreign keys

Referential integrity

yes

links between datasets can be stored

Transaction concepts

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

yes

Atomic single-row operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

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

yes

based on H2

yes

More information provided by the system vendor

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More resources

DB-Engines blog posts

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