scaliendb VS ClickHouse

Hey man, don't worry, it will be all right!

About ~10 years ago in 2012-2013, within a ~6 month period (i) my startup [1] which I've been doing for 4 years failed / we shut it down (ii) my wife left, and a few months later told me that she'd been cheating on me.

There was a ~6 month period when I was very depressed, sometimes I wasn't able to sleep for multiple nights in a row, even when I got sleep, it was a few hours at best. It was a truly terrible period, I felt humiliated and reduced to nothing. I looked at my friends with stable boring jobs and families and thought that I messed up big time. I was so depressed, I even went to church a couple of times Sunday morning, because I couldn't sleep and I felt so sorry for myself, even though I'm an agnostic physicist.

Then something really unexpected happened: I got a job at a successful startup [2], which had great culture and people, and suddenly I was partying 2x a week with great people. While I was doing my own startup I stopped doing sports, so I picked up a +15 kg. The depression helped me lose most of it, and since I suddenly had a lot of free-time (no startup, no wife), I started doing sports again [3]. Even more unexpected, being divorced turned out to be appealing to ladies (I jokingly call it the "wounded deer" phenomenon), so I suddenly had ladies sending me signals.

Overall, in another ~6 months, to my huge surprise, there was a huge turn-around in my life, and in the end 2013 became one of the best years in my life! It was super-surprising, because it started on such a downer (Jan-6 was when my wife told me it's over, next day she moved out), but by Q3 I was hooked up with my girlfriend [4], feeling super happy at work and I even did another Ironman that year!

So... it's completely normal to feel depressed in such situations. Just give it some time, build yourself up, and find a good social situation. I personally also started a Phd, which I didn't finish because of the aforementioned startup, but I don't want to tell you to do that. You can potentially create positive vibes around you even by going to a co-working place 2x a week, doing some team sports, etc.

-

[1] https://github.com/scalien/scaliendb

Yes, we are working on it! :) Taking some of the learnings from current experimental JSON Object datatype, we are now working on what will become the production-ready implementation. Details here: https://github.com/ClickHouse/ClickHouse/issues/54864

Variant datatype is already available as experimental in 24.1, Dynamic datatype is WIP (PR almost ready), and JSON datatype is next up. Check out the latest comment on that issue with how the Dynamic datatype will work: https://github.com/ClickHouse/ClickHouse/issues/54864#issuec...

In our repository, I've set up a few hard limits: each translation unit cannot spend more than a certain amount of memory for compilation and a certain amount of CPU time, and the compiled binary has to be not larger than a certain size.

When these limits are reached, the CI stops working, and we have to remove the bloat: https://github.com/ClickHouse/ClickHouse/issues/61121

Although these limits are too generous as of today: for example, the maximum CPU time to compile a translation unit is set to 1000 seconds, and the memory limit is 5 GB, which is ridiculously high.

I have a project dedicated to this topic: https://github.com/ClickHouse/ClickBench

It is important to explain the limitations of a benchmark, provide a methodology, and make it reproducible. It also has to be simple enough, otherwise it will not be realistic to include a large number of participants.

I'm also collecting all database benchmarks I could find: https://github.com/ClickHouse/ClickHouse/issues/22398

ClickHouse: A fast open-source column-oriented database management system. ClickHouse is designed for real-time analytics on large datasets and excels in high-speed data insertion and querying, making it ideal for real-time monitoring and reporting.

Today we're going to create an UDF (User-defined Function) in Golang that can be run inside Clickhouse query, this function will parse uuid v1 and return timestamp of it since Clickhouse doesn't have this function for now. Inspired from the python version with TabSeparated delimiter (since it's easiest to parse), UDF in Clickhouse will read line by line (each row is each line, and each text separated with tab is each column/cell value):

For the third, examples here might be analytics plugins in specialized databases like Clickhouse, data-transformations in places like your ETL pipeline using Airflow or Fivetran, or special integrations in your authentication workflow with Auth0 hooks and rules.

Online analytical processing (OLAP) databases like Apache Druid, Apache Pinot, and ClickHouse shine in addressing user-initiated analytical queries. You might write a query to analyze historical data to find the most-clicked products over the past month efficiently using OLAP databases. When contrasting with streaming databases, they may not be optimized for incremental computation, leading to challenges in maintaining the freshness of results. The query in the streaming database focuses on recent data, making it suitable for continuous monitoring. Using streaming databases, you can run queries like finding the top 10 sold products where the “top 10 product list” might change in real-time.

Proton is a lightweight streaming processing "add-on" for ClickHouse, and we are making these delta parts as standalone as possible. Meanwhile contributing back to the ClickHouse community can also help a lot.

Please check this PR from the proton team: https://github.com/ClickHouse/ClickHouse/pull/54870

curl https://clickhouse.com/ | sh

But I continue to find garbage in some of our CI scripts.

Here is an example: https://github.com/ClickHouse/ClickHouse/pull/58794/files

The right way is to:

- always pin versions of all packages;