DBMS > BigchainDB vs. LevelDB vs. MySQL vs. OrigoDB vs. Transbase

System Properties Comparison BigchainDB vs. LevelDB vs. MySQL vs. OrigoDB vs. Transbase

Editorial information provided by DB-Engines

Name

Description

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

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

Widely used open source RDBMS

A fully ACID in-memory object graph database

A resource-optimized, high-performance, universally applicable RDBMS

Primary database model

Document store

Key-value store

Relational DBMS

Key/Value like access via memcached API

Document store
Object oriented DBMS

Relational DBMS

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	2.25
Rank	#115	Overall
	#19	Key-value stores

Score	1061.34
Rank	#2	Overall
	#2	Relational DBMS

Score	0.06
Rank	#380	Overall
	#50	Document stores
	#18	Object oriented DBMS

Score	0.17
Rank	#334	Overall
	#148	Relational DBMS

Website

www.bigchaindb.com

github.com/google/leveldb

www.mysql.com

origodb.com

www.transaction.de/en/products/transbase.html

Technical documentation

bigchaindb.readthedocs.io/en/latest

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

dev.mysql.com/doc

origodb.com/docs

www.transaction.de/en/products/transbase/features.html

Developer

Google

Oracle

since 2010, originally MySQL AB, then Sun

Robert Friberg et al

Transaction Software GmbH

Initial release

2016

2011

1995

2009

under the name LiveDB

1987

Current release

1.23, February 2021

8.4.0, April 2024

Transbase 8.3, 2022

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

BSD

Open Source

GPL version 2. Commercial licenses with extended functionallity are available

Open Source

commercial

free development license

Cloud-based only

Only available as a cloud service

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Implementation language

Python

C++

C and C++

Server operating systems

Linux

Illumos
Linux
OS X
Windows

FreeBSD
Linux
OS X
Solaris
Windows

Linux
Windows

FreeBSD
Linux
macOS
Solaris
Windows

Data scheme

schema-free

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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

can be achieved using .NET

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

yes

APIs and other access methods

CLI Client
RESTful HTTP API

ADO.NET
JDBC
ODBC
Proprietary native API

.NET Client API
HTTP API
LINQ

ADO.NET
JDBC
ODBC
Proprietary native API

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

C++
Go
Java

3rd party binding
JavaScript (Node.js)

3rd party binding
Python

3rd party binding

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++
Java
JavaScript
Kotlin
Objective-C
PHP
Python

Server-side scripts

Stored procedures

yes

proprietary syntax

yes

Triggers

yes

Domain Events

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

horizontal partitioning, sharding with MySQL Cluster or MySQL Fabric

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

none

Multi-source replication
Source-replica replication

Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

depending on model

yes

Transaction concepts

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

ACID

not for MyISAM storage engine

ACID

yes

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

with automatic compression on writes

yes

Write ahead log

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

Users with fine-grained authorization concept

no user groups or roles

Role based authorization

fine grained access rights according to SQL-standard

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