DBMS > BigchainDB vs. ClickHouse vs. H2 vs. RethinkDB

System Properties Comparison BigchainDB vs. ClickHouse vs. H2 vs. RethinkDB

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Editorial information provided by DB-Engines

Name

Description

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

A high-performance, column-oriented SQL DBMS for online analytical processing (OLAP) that uses all available system resources to their full potential to process each analytical query as fast as possible. It is available as both an open-source software and a cloud offering.

Full-featured RDBMS with a small footprint, either embedded into a Java application or used as a database server.

DBMS for the Web with a mechanism to push updated query results to applications in realtime.

Primary database model

Document store

Relational DBMS

Document store

Secondary database models

Time Series DBMS

Spatial DBMS

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

Score	0.79
Rank	#212	Overall
	#36	Document stores

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	8.13
Rank	#49	Overall
	#31	Relational DBMS

Score	2.74
Rank	#105	Overall
	#19	Document stores

Website

Technical documentation

bigchaindb.readthedocs.io/en/latest

clickhouse.com/docs

www.h2database.com/html/main.html

rethinkdb.com/docs

Developer

Clickhouse Inc.

Thomas Mueller

The Linux Foundation

since July 2017

Initial release

2016

2005

2009

Current release

v24.4.1.2088-stable, May 2024

2.2.220, July 2023

2.4.1, August 2020

License

Commercial or Open Source

Open Source

AGPL v3

Open Source

Apache 2.0

Open Source

dual-licence (Mozilla public license, Eclipse public license)

Open Source

Apache Version 2

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.

ClickHouse Cloud: Get the performance you love from open source ClickHouse in a serverless offering that takes care of the details so you can spend more time getting insight out of the fastest database on earth.
Aiven for Clickhouse: Managed cloud data warehousing with high-speed analytics.
DoubleCloud: Fully managed ClickHouse alongside best-in-class managed open-source services to build analytics at scale.

Implementation language

Python

C++

Java

C++

Server operating systems

Linux

FreeBSD
Linux
macOS

All OS with a Java VM

Linux
OS X
Windows

Data scheme

schema-free

yes

schema-free

Typing

predefined data types such as float or date

yes

string, binary, float, bool, date, geometry

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

Close to ANSI SQL (SQL/JSON + extensions)

yes

APIs and other access methods

CLI Client
RESTful HTTP API

gRPC
HTTP REST
JDBC
MySQL wire protocol
ODBC
PostgreSQL wire protocol
Proprietary protocol

JDBC
ODBC

Supported programming languages

Go
Haskell
Java
JavaScript
Python
Ruby

3rd party library
C++
Elixir

3rd party library
Go

3rd party library
Java

3rd party library
JavaScript (Node.js)

3rd party library
Kotlin

3rd party library
Nim

3rd party library
Perl

3rd party library
PHP

3rd party library
Python

3rd party library
R

3rd party library
Ruby

3rd party library
Rust
Scala

3rd party library

Java

community-supported driver
C#

community-supported driver
C++

community-supported driver
Clojure

community-supported driver
Dart

community-supported driver
Erlang

community-supported driver
Go

community-supported driver
Haskell

community-supported driver
Java

official driver
JavaScript (Node.js)

official driver
Lisp

community-supported driver
Lua

community-supported driver
Objective-C

community-supported driver
Perl

community-supported driver
PHP

community-supported driver
Python

official driver
Ruby

official driver
Scala

community-supported driver

Server-side scripts

Stored procedures

yes

Java Stored Procedures and User-Defined Functions

Triggers

yes

Client-side triggers through changefeeds

Partitioning methods

Methods for storing different data on different nodes

Sharding

key based and custom

none

Sharding

range based

Replication methods

Methods for redundantly storing data on multiple nodes

selectable replication factor

Asynchronous and synchronous physical replication; geographically distributed replicas; support for object storages.

With clustering: 2 database servers on different computers operate on identical copies of a database

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

Foreign keys

Referential integrity

yes

Transaction concepts

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

ACID

Atomic single-document operations

Concurrency

Support for concurrent manipulation of data

yes

yes, multi-version concurrency control (MVCC)

yes

MVCC based

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

Access rights for users and roles. Column and row based policies. Quotas and resource limits. Pluggable authentication with LDAP and Kerberos. Password based, X.509 certificate, and SSH key authentication.

fine grained access rights according to SQL-standard

yes

users and table-level permissions

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