DBMS > Firebase Realtime Database vs. Oracle Berkeley DB vs. RethinkDB vs. SQLite

System Properties Comparison Firebase Realtime Database vs. Oracle Berkeley DB vs. RethinkDB vs. SQLite

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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.

Widely used in-process key-value store

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

Widely used embeddable, in-process RDBMS

Primary database model

Document store

Key-value store

supports sorted and unsorted key sets
Native XML DBMS

in the Oracle Berkeley DB XML version

Document store

Relational DBMS

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	2.21
Rank	#117	Overall
	#20	Key-value stores
	#3	Native XML DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Score	114.32
Rank	#10	Overall
	#7	Relational DBMS

Website

firebase.google.com/products/realtime-database

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

rethinkdb.com

www.sqlite.org

Technical documentation

firebase.google.com/docs/database

docs.oracle.com/cd/E17076_05/html/index.html

rethinkdb.com/docs

www.sqlite.org/docs.html

Developer

Google

acquired by Google 2014

Oracle

originally developed by Sleepycat, which was acquired by Oracle

The Linux Foundation

since July 2017

Dwayne Richard Hipp

Initial release

2012

1994

2009

2000

Current release

18.1.40, May 2020

2.4.1, August 2020

3.45.3 (15 April 2024), April 2024

License

Commercial or Open Source

commercial

Open Source

commercial license available

Open Source

Apache Version 2

Open Source

Public Domain

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

C, Java, C++ (depending on the Berkeley DB edition)

C++

Server operating systems

hosted

AIX
Android
FreeBSD
iOS
Linux
OS X
Solaris
VxWorks
Windows

Linux
OS X
Windows

server-less

Data scheme

schema-free

yes

dynamic column types

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

yes

not rigid because of 'dynamic typing' concept.

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

only with the Berkeley DB XML edition

Secondary indexes

yes

SQL

Support of SQL

yes

SQL interfaced based on SQLite is available

yes

SQL-92 is not fully supported

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET

inofficial driver
JDBC

inofficial driver
ODBC

inofficial driver

Supported programming languages

Java
JavaScript
Objective-C

.Net

Figaro is a .Net framework assembly that extends Berkeley DB XML into an embeddable database engine for .NET
others

Third-party libraries to manipulate Berkeley DB files are available for many languages
C
C#
C++
Java
JavaScript (Node.js)

3rd party binding
Perl
Python
Tcl

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

Actionscript
Ada
Basic
C
C#
C++
D
Delphi
Forth
Fortran
Haskell
Java
JavaScript
Lisp
Lua
MatLab
Objective-C
OCaml
Perl
PHP
PL/SQL
Python
R
Ruby
Scala
Scheme
Smalltalk
Tcl

Server-side scripts

Stored procedures

limited functionality with using 'rules'

Triggers

Callbacks are triggered when data changes

yes

only for the SQL API

Client-side triggers through changefeeds

yes

Partitioning methods

Methods for storing different data on different nodes

none

Sharding

range based

none

Replication methods

Methods for redundantly storing data on multiple nodes

Source-replica replication

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

yes

ACID

Atomic single-document operations

ACID

Concurrency

Support for concurrent manipulation of data

yes

MVCC based

yes

via file-system locks

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

users and table-level permissions

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