DBMS > BigchainDB vs. Cubrid vs. GeoMesa vs. Vitess

System Properties Comparison BigchainDB vs. Cubrid vs. GeoMesa vs. Vitess

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Editorial information provided by DB-Engines

Name

Description

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

CUBRID is an open-source SQL-based relational database management system with object extensions for OLTP

GeoMesa is a distributed spatio-temporal DBMS based on various systems as storage layer.

Scalable, distributed, cloud-native DBMS, extending MySQL

Primary database model

Secondary database models

Document store
Spatial DBMS

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	1.20
Rank	#169	Overall
	#78	Relational DBMS

Score	0.78
Rank	#213	Overall
	#4	Spatial DBMS

Score	0.82
Rank	#209	Overall
	#97	Relational DBMS

Website

www.bigchaindb.com

cubrid.com (korean)
cubrid.org (english)

www.geomesa.org

vitess.io

Technical documentation

bigchaindb.readthedocs.io/en/latest

cubrid.org/manuals

www.geomesa.org/documentation/stable/user/index.html

vitess.io/docs

Developer

CUBRID Corporation, CUBRID Foundation

CCRi and others

The Linux Foundation, PlanetScale

Initial release

2016

2008

2014

2013

Current release

11.0, January 2021

4.0.5, February 2024

15.0.2, December 2022

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

Apache Version 2.0

Open Source

Apache License 2.0

Open Source

Apache Version 2.0, commercial licenses available

Cloud-based only

Only available as a cloud service

DBaaS offerings (sponsored links)

Database as a Service

Providers of DBaaS offerings, please contact us to be listed.

Implementation language

Python

C, C++, Java

Scala

Server operating systems

Linux

Linux
Windows

Docker
Linux
macOS

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.

Secondary indexes

yes

SQL

Support of SQL

yes

with proprietary extensions

APIs and other access methods

CLI Client
RESTful HTTP API

ADO.NET
JDBC
ODBC
OLE DB

ADO.NET
JDBC
MySQL protocol
ODBC

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

C
C#
C++
Go
Java
JavaScript (Node.js)
Perl
PHP
Python
Ruby

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

Server-side scripts

Stored procedures

Java Stored Procedures

yes

proprietary syntax

Triggers

yes

Partitioning methods

Methods for storing different data on different nodes

Sharding

none

depending on storage layer

Sharding

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Source-replica replication

depending on storage layer

Multi-source replication
Source-replica replication

MapReduce

Offers an API for user-defined Map/Reduce methods

yes

Consistency concepts

Methods to ensure consistency in a distributed system

Immediate Consistency

depending on storage layer

Eventual Consistency across shards
Immediate Consistency within a shard

Foreign keys

Referential integrity

yes

not for MyISAM storage engine

Transaction concepts

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

ACID

ACID at shard level

Concurrency

Support for concurrent manipulation of data

yes

table locks or row locks depending on storage engine

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.

depending on storage layer

yes

User concepts

Access control

yes

fine grained access rights according to SQL-standard

yes

depending on the DBMS used for storage

Users with fine-grained authorization concept

no user groups or roles

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More resources

DB-Engines blog posts

Spatial database management systems
6 April 2021, Matthias Gelbmann

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Recent citations in the news

An Introduction to BigchainDB, a Popular Blockchain Database
17 September 2020, Open Source For You

Exploring the 10 BEST Python Libraries for Blockchain Applications
9 September 2023, DataDrivenInvestor

Blockchain Database Startup BigchainDB Raises €3 Million
27 September 2016, CoinDesk

Using BigchainDB: A Database with Blockchain Characteristics
20 January 2022, Open Source For You

What is BigchainDB Technology & How it works and the Characteristics?
26 August 2017, Blockchain Council

provided by Google News

Vitess, the database clustering system powering YouTube, graduates CNCF incubation
5 November 2019, SiliconANGLE News

PlanetScale Unveils Distributed MySQL Database Service Based on Vitess
18 May 2021, Datanami

PlanetScale grabs YouTube-developed open-source tech, promises Vitess DBaaS with on-the-fly schema changes
18 May 2021, The Register

They scaled YouTube — now they’ll shard everyone with PlanetScale
13 December 2018, TechCrunch

Massively Scaling MySQL Using Vitess
19 February 2019, InfoQ.com

provided by Google News

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