Intro to ClickHouse by Tinybird - Setup, basic SQL commands, engines, partitions and internals

Tinybird is built on top of ClickHouse, a very fast and performant OLAP database. But like many "fast machines", Clickhouse is complex! Our goal at Tinybird is to make it easy for any developer to build applications over huge amounts of data without having to become Clickhouse experts.

But to do that, we at Tinybird need to understand in depth how ClickHouse works. This video is a recording of one of our onboarding sessions for employees where Javi Santana, our cofounder, goes over the basics of how to run ClickHouse and how it stores data internally, among other important topics (the video is in Spanish)

00:00:00 What is this and why we're doing it
00:01:14 Setup: installing ClickHouse and the commands we use the most
00:08:05 Running the ClickHouse server on localhost and connecting to it with the CH client
00:12:18 Creating tables, inserting data and types of engines available
00:19:51 MergeTree: ClickHouse's most used engine. Sorting keys.
00:26:18 How ClickHouse stores data internally. Data parts, automatic and manual merging and `optimize table` command
00:34:01 Data compression. CPU and memory considerations on whether to compress data or not. Compression algorithms
00:38:09 ClickHouse VS ElasticSearch. Is Elastic a viable option to do real-time analytics on billions of rows of structured data?
00:40:50 Partitions. How they're managed internally and what they're useful for
00:45:54 MRK files and range indexes
00:48:27 ClickHouse server configuration
00:49:20 Inserting CSV data
00:51:50 ClickHouse HTTP interface
00:55:00 Q&A - Moving data across servers, attach command
00:57:46 Q&A - Having multiple indexes for the same dataset & materialized views on ClickHouse