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Clickhouse
What is ClickHouse?
ClickHouse is an open-source column-oriented DBMS for online analytical processing (OLAP) that allows users to generate analytical reports using SQL queries in real-time.
Its technology works 100-1000x faster than traditional database management systems and processes hundreds of millions to over a billion rows and tens of gigabytes of data per server per second. With a widespread user base around the globe, the technology has received praise for its reliability, ease of use, and fault tolerance.
ClickHouse differs from the regular traditional OLTP row oriented DBMS – MySQL, MS SQL Server, PostgreSQL
Features List
- 100-1000x faster than traditional database management systems
- Processes hundreds of millions to over a billion rows and tens of gigabytes of data per server per second
- Reliability, ease of use, and fault tolerance.
- True column-oriented DBMS.
- Linear scalability – It’s possible to extend a cluster by adding servers.
- SQL support – ClickHouse supports an extended SQL-like language that includes arrays and nested data structures, approximate and URI functions, and the availability to connect an external key-value store.
- Hard disk drive (HDD) optimization.
- Clients for database (DB) connectivity. Database connection options include the console client, the HTTP API, or one of the wrappers (wrappers are available for Python, PHP, NodeJS, Perl, Ruby and R. ODBC driver and JDBC driver are also available for ClickHouse.
Open Source Community
- The click house community
- Developers, Users
- Volunteers and Professionals
- Great members support from all over the world
Development Life Cycle
- Developer(s) ClickHouse, Inc. Yandex
- Initial release – June 15, 2016; 5 years ago
- Stable release – v22.1.2.2-stable / January 19, 2022
License
- Apache License 2.0
- Applies to every part (module, product, option) of mysql
- Permission to copy, modify, distribute and documents without fee.
- Completely 100% open source
Security and Data Protection
- Enterprise grade security features
- Fail-safe mechanisms protecting against data corruption from application bugs and human errors
Business Continuity
- Reliability and Data Integrity
- Scalable
- Sharing
- Replica
- Data safety – backup/recovery
- Distributed table
Limitations
- There is no support for transactions.
- Lack of full-fledged UPDATE/DELETE implementation.
Use cases
- Yandex
- Uber
- Ebay
- CLOUDFLARE
- Spotify
- Deutsche Bank
