DBMS > Firebase Realtime Database vs. H2GIS vs. Oracle Rdb vs. Riak TS

System Properties Comparison Firebase Realtime Database vs. H2GIS vs. Oracle Rdb vs. Riak TS

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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.

Spatial extension of H2

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

Primary database model

Secondary database models

Relational DBMS

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

Score	15.00
Rank	#39	Overall
	#6	Document stores

Score	0.05
Rank	#372	Overall
	#7	Spatial DBMS

Score	1.08
Rank	#187	Overall
	#85	Relational DBMS

Score	0.25
Rank	#308	Overall
	#26	Time Series DBMS

Website

firebase.google.com/products/realtime-database

www.h2gis.org

www.oracle.com/database/technologies/related/rdb.html

Technical documentation

firebase.google.com/docs/database

www.h2gis.org/docs/home

www.oracle.com/database/technologies/related/rdb-doc.html

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

Developer

Google

acquired by Google 2014

CNRS

Oracle, originally developed by Digital Equipment Corporation (DEC)

Open Source, formerly Basho Technologies

Initial release

2012

2013

1984

2015

Current release

7.4.1.1, 2021

3.0.0, September 2022

License

Commercial or Open Source

commercial

Open Source

LGPL 3.0

commercial

Open Source

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

Server operating systems

hosted

HP Open VMS

Linux
OS X

Data scheme

schema-free

yes

Flexible Schema (defined schema, partial schema, schema free)

schema-free

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

HTTP API
Native Erlang Interface

Supported programming languages

Java
JavaScript
Objective-C

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

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

based on H2

Erlang

Triggers

Callbacks are triggered when data changes

yes

pre-commit hooks and post-commit hooks

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

yes

based on H2

selectable replication factor

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

Eventual 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

ACID

yes, on a single node

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

yes

based on H2

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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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