DBMS > Firebase Realtime Database vs. MySQL vs. OrientDB vs. TerminusDB vs. Trafodion

System Properties Comparison Firebase Realtime Database vs. MySQL vs. OrientDB vs. TerminusDB vs. Trafodion

Editorial information provided by DB-Engines

Name

Apache Trafodion has been retired in 2021. Therefore it is excluded from the DB-Engines Ranking.

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 open source RDBMS

Multi-model DBMS (Document, Graph, Key/Value)

Scalable Graph Database platform making enterprise data available by exploiting inferred entities and relationships

Transactional SQL-on-Hadoop DBMS

Primary database model

Document store

Relational DBMS

Key/Value like access via memcached API

Document store
Graph DBMS
Key-value store

Graph DBMS

Relational DBMS

Secondary database models

Document store
Spatial DBMS

Document store
RDF store

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

Score	14.29
Rank	#39	Overall
	#6	Document stores

Score	1083.74
Rank	#2	Overall
	#2	Relational DBMS

Score	3.19
Rank	#93	Overall
	#16	Document stores
	#7	Graph DBMS
	#14	Key-value stores

Score	0.17
Rank	#325	Overall
	#29	Graph DBMS

Website

firebase.google.com/products/realtime-database

Technical documentation

firebase.google.com/docs/database

dev.mysql.com/doc

www.orientdb.com/docs/last/index.html

terminusdb.github.io/terminusdb/#

trafodion.apache.org/documentation.html

Developer

Google

acquired by Google 2014

Oracle

since 2010, originally MySQL AB, then Sun

OrientDB LTD; CallidusCloud; SAP

DataChemist Ltd.

Apache Software Foundation, originally developed by HP

Initial release

2012

1995

2010

2018

2014

Current release

8.4.0, April 2024

3.2.29, March 2024

11.0.0, January 2023

2.3.0, February 2019

License

Commercial or Open Source

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

Apache version 2

Open Source

GPL V3

Open Source

Apache 2.0

Cloud-based only

Only available as a cloud service

yes

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Implementation language

C and C++

Java

Prolog, Rust

C++, Java

Server operating systems

hosted

FreeBSD
Linux
OS X
Solaris
Windows

All OS with a Java JDK (>= JDK 6)

Linux

Data scheme

schema-free

yes

schema-free

Schema can be enforced for whole record ("schema-full") or for some fields only ("schema-hybrid")

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

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

SQL-like query language, no joins

SQL-like query language (WOQL)

yes

APIs and other access methods

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

Tinkerpop technology stack with Blueprints, Gremlin, Pipes
Java API
RESTful HTTP/JSON API

OWL
RESTful HTTP API
WOQL (Web Object Query Language)

ADO.NET
JDBC
ODBC

Supported programming languages

Java
JavaScript
Objective-C

Ada
C
C#
C++
D
Delphi
Eiffel
Erlang
Haskell
Java
JavaScript (Node.js)
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net
C
C#
C++
Clojure
Java
JavaScript
JavaScript (Node.js)
PHP
Python
Ruby
Scala

JavaScript
Python

All languages supporting JDBC/ODBC/ADO.Net

Server-side scripts

Stored procedures

limited functionality with using 'rules'

yes

proprietary syntax

Java, Javascript

yes

Java Stored Procedures

Triggers

Callbacks are triggered when data changes

yes

Hooks

yes

Partitioning methods

Methods for storing different data on different nodes

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

Graph Partitioning

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

Multi-source replication
Source-replica replication

Multi-source replication

Journaling Streams

yes, via HBase

MapReduce

Offers an API for user-defined Map/Reduce methods

could be achieved with distributed queries

yes

via user defined functions and HBase

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

not for MyISAM storage engine

yes

relationship in graphs

yes

Transaction concepts

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

yes

ACID

not for MyISAM storage engine

ACID

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

yes

Durability

Support for making data persistent

yes

in-memory journaling

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

Users with fine-grained authorization concept

no user groups or roles

Access rights for users and roles; record level security configurable

Role-based access control

fine grained access rights according to SQL-standard

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