DBMS > ClickHouse vs. Databricks vs. Infobright vs. OrigoDB

System Properties Comparison ClickHouse vs. Databricks vs. Infobright vs. OrigoDB

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Editorial information provided by DB-Engines

Name

Description

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.

The Databricks Lakehouse Platform combines elements of data lakes and data warehouses to provide a unified view onto structured and unstructured data. It is based on Apache Spark.

High performant column-oriented DBMS for analytic workloads using MySQL or PostgreSQL as a frontend

A fully ACID in-memory object graph database

Primary database model

Relational DBMS

Document store
Relational DBMS

Relational DBMS

Document store
Object oriented DBMS

Secondary database models

Time Series DBMS

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

Score	16.34
Rank	#38	Overall
	#23	Relational DBMS

Score	78.61
Rank	#15	Overall
	#2	Document stores
	#10	Relational DBMS

Score	0.96
Rank	#194	Overall
	#91	Relational DBMS

Score	0.00
Rank	#383	Overall
	#53	Document stores
	#20	Object oriented DBMS

Website

clickhouse.com

www.databricks.com

ignitetech.com/softwarelibrary/infobrightdb

origodb.com

Technical documentation

clickhouse.com/docs

docs.databricks.com

origodb.com/docs

Developer

Clickhouse Inc.

Databricks

Ignite Technologies Inc.; formerly InfoBright Inc.

Robert Friberg et al

Initial release

2016

2013

2005

2009

under the name LiveDB

Current release

v24.4.1.2088-stable, May 2024

License

Commercial or Open Source

Open Source

Apache 2.0

commercial

The open source (GPLv2) version did not support inserts/updates/deletes and was discontinued with July 2016

Open Source

Cloud-based only

Only available as a cloud service

yes

DBaaS offerings (sponsored links)

Database as a Service

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

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.
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.

Implementation language

C++

Server operating systems

FreeBSD
Linux
macOS

hosted

Linux
Windows

Data scheme

yes

Flexible Schema (defined schema, partial schema, schema free)

yes

Typing

predefined data types such as float or date

yes

User defined using .NET types and collections

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

Knowledge Grid Technology used instead

yes

SQL

Support of SQL

Close to ANSI SQL (SQL/JSON + extensions)

with Databricks SQL

yes

APIs and other access methods

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

JDBC
ODBC
RESTful HTTP API

ADO.NET
JDBC
ODBC

.NET Client API
HTTP API
LINQ

Supported programming languages

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

Python
R
Scala

.Net
C
C#
C++
D
Eiffel
Erlang
Haskell
Java
Objective-C
OCaml
Perl
PHP
Python
Ruby
Scheme
Tcl

.Net

Server-side scripts

Stored procedures

yes

user defined functions and aggregates

yes

Triggers

yes

Domain Events

Partitioning methods

Methods for storing different data on different nodes

key based and custom

none

horizontal partitioning

client side managed; servers are not synchronized

Replication methods

Methods for redundantly storing data on multiple nodes

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

yes

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

depending on model

Transaction concepts

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

ACID

Concurrency

Support for concurrent manipulation of data

yes

Durability

Support for making data persistent

yes

Write ahead log

In-memory capabilities

Is there an option to define some or all structures to be held in-memory only.

yes

User concepts

Access control

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

exploiting MySQL or PostgreSQL frontend capabilities

Role based authorization

More information provided by the system vendor

Specific characteristics

Supported database models : In addition to the Document store and Relational DBMS...
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