DBMS > Firebase Realtime Database vs. LevelDB vs. Oracle Rdb vs. Postgres-XL

System Properties Comparison Firebase Realtime Database vs. LevelDB vs. Oracle Rdb vs. Postgres-XL

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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.

Embeddable fast key-value storage library that provides an ordered mapping from string keys to string values

Based on PostgreSQL enhanced with MPP and write-scale-out cluster features

Primary database model

Document store

Key-value store

Relational DBMS

Secondary database models

Document store
Spatial DBMS

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

Score	13.60
Rank	#39	Overall
	#6	Document stores

Score	2.33
Rank	#111	Overall
	#19	Key-value stores

Score	1.04
Rank	#184	Overall
	#84	Relational DBMS

Score	0.43
Rank	#260	Overall
	#119	Relational DBMS

Website

firebase.google.com/products/realtime-database

github.com/google/leveldb

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

www.postgres-xl.org

Technical documentation

firebase.google.com/docs/database

github.com/google/leveldb/blob/main/doc/index.md

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

www.postgres-xl.org/documentation

Developer

Google

acquired by Google 2014

Google

Oracle, originally developed by Digital Equipment Corporation (DEC)

Initial release

2012

2011

1984

2014

since 2012, originally named StormDB

Current release

1.23, February 2021

7.4.1.1, 2021

10 R1, October 2018

License

Commercial or Open Source

commercial

Open Source

BSD

commercial

Open Source

Mozilla public license

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++

Server operating systems

hosted

Illumos
Linux
OS X
Windows

HP Open VMS

Linux
macOS

Data scheme

schema-free

Flexible Schema (defined schema, partial schema, 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.

yes

XML type, but no XML query functionality

Secondary indexes

yes

SQL

Support of SQL

yes

distributed, parallel query execution

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET
JDBC
native C library
ODBC
streaming API for large objects

Supported programming languages

Java
JavaScript
Objective-C

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

.Net
C
C++
Delphi
Erlang
Java
JavaScript (Node.js)
Perl
PHP
Python
Tcl

Server-side scripts

Stored procedures

limited functionality with using 'rules'

user defined functions

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

none

horizontal partitioning

Replication methods

Methods for redundantly storing data on multiple nodes

none

MapReduce

Offers an API for user-defined Map/Reduce methods

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

yes, on a single node

ACID

MVCC

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

with automatic compression on writes

yes

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

User concepts

Access control

yes, based on authentication and database rules

fine grained access rights according to SQL-standard

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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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