DBMS > BigchainDB vs. Firebase Realtime Database vs. GBase vs. MySQL vs. TypeDB

System Properties Comparison BigchainDB vs. Firebase Realtime Database vs. GBase vs. MySQL vs. TypeDB

Editorial information provided by DB-Engines

Name

Description

BigchainDB is scalable blockchain database offering decentralization, immutability and native assets

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 RDBMS in China, including analytical, transactional, distributed transactional, and cloud-native data warehousing.

Widely used open source RDBMS

TypeDB is a strongly-typed database with a rich and logical type system and TypeQL as its query language

Primary database model

Document store

Relational DBMS

Key/Value like access via memcached API

Graph DBMS
Relational DBMS

Often described as a 'hyper-relational' database, since it implements the 'Entity-Relationship Paradigm' to manage complex data structures and ontologies.

Secondary database models

Document store
Spatial DBMS

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

Score	0.85
Rank	#208	Overall
	#35	Document stores

Score	13.64
Rank	#39	Overall
	#6	Document stores

Score	1.05
Rank	#186	Overall
	#86	Relational DBMS

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	0.70
Rank	#230	Overall
	#20	Graph DBMS
	#106	Relational DBMS

Website

www.bigchaindb.com

firebase.google.com/products/realtime-database

www.gbase.cn

www.mysql.com

typedb.com

Technical documentation

bigchaindb.readthedocs.io/en/latest

firebase.google.com/docs/database

dev.mysql.com/doc

typedb.com/docs

Developer

Google

acquired by Google 2014

General Data Technology Co., Ltd.

Oracle

since 2010, originally MySQL AB, then Sun

Vaticle

Initial release

2016

2012

2004

1995

2016

Current release

GBase 8a, GBase 8s, GBase 8c

8.4.0, April 2024

2.26.3, January 2024

License

Commercial or Open Source

Open Source

AGPL v3

commercial

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

GPL Version 3, commercial licenses available

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

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Implementation language

Python

C, Java, Python

C and C++

Java

Server operating systems

Linux

hosted

Linux

FreeBSD
Linux
OS X
Solaris
Windows

Linux
OS X
Windows

Data scheme

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

Secondary indexes

yes

SQL

Support of SQL

Standard with numerous extensions

yes

with proprietary extensions

APIs and other access methods

CLI Client
RESTful HTTP API

Android
iOS
JavaScript API
RESTful HTTP API

ADO.NET
C API
JDBC
ODBC

ADO.NET
JDBC
ODBC
Proprietary native API

gRPC protocol
TypeDB Console (shell)
TypeDB Studio (Visualisation software- previously TypeDB Workbase)

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

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

All JVM based languages
Groovy
Java
JavaScript (Node.js)
Python
Scala

Server-side scripts

Stored procedures

limited functionality with using 'rules'

user defined functions

yes

proprietary syntax

Triggers

Callbacks are triggered when data changes

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

horizontal partitioning (by range, list and hash) and vertical partitioning

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

Sharding

by using Cassandra

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

yes

Multi-source replication
Source-replica replication

Multi-source replication

by using Cassandra

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

by using Apache Kafka and Apache Zookeeper

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

substituted by the relationship feature

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,with MongoDB ord RethinkDB

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

yes, based on authentication and database rules

yes

Users with fine-grained authorization concept

no user groups or roles

yes

at REST API level; other APIs in progress

More information provided by the system vendor

Specific characteristics

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Competitive advantages

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Typical application scenarios

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Licensing and pricing models

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