ClickHouse VS PostHog

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;

It would be a shame not to mention PostHog as the telemetry provider we are using, since it turned out to be extremely useful. Because it is hard to find people who will talk with you about your product, gathering statistics gave us a much greater insight into our users.

6- PostHog

Hi HN, PostHog employee here. I'm working on our Web Analytics product, which is currently in beta. It's fun to see us mentioned here :)

I should mention that we have a ton of SDKs (see https://posthog.com/docs/libraries) for back end frameworks and languages, so if you wanted to use PostHog without any client-side JS you could send pageviews and other events manually, but for the vast majority of people it makes more sense to use our JS snippet.

Hijacking this comment to share the roadmap for web analytics https://github.com/PostHog/posthog/issues/18547. It's very much in the launch-early-and-be-embarassed phase, but I would love to hear any feedback or suggestions that people have, particularly if you're already a PostHog user.

how's this different than https://posthog.com/ ?

PostHog - Open Source Alternative to Mixpanel

Don't insert the logs/events/analytics into your Application DB. Usually, you send those to specialist datastores (OLAP etc) that process such high volume of data. You can use something like clickhouse [0] for example or use 3rd party SAAS solutions like posthog [1] etc that are built on top of clickhouse

[0] https://clickhouse.com

[1] https://posthog.com

I may use Flask-Admin initially to offload the "CRUD" operations to have an initial prototype fast but then drop it ASAP because I don't want to write a "flask-admin application" to fight against later on. If the application is mainly "CRUD", then Flask-Admin is suitable.

Now...

Would you do a breakdown/list of all the jobs you've done by sector/vertical and by function/role and by application functionality?

- [0]: https://flask.palletsprojects.com

- [1]: https://flask-admin.readthedocs.io/en/latest

- [2]: https://flask.palletsprojects.com/en/2.3.x/patterns/celery

- [3]: https://sentry.io

- [4]: https://posthog.com

- [5]: https://www.docker.com

PostHog | Remote (US/Europe timezones) | Full stack engineer, technical ex-founder, tech lead | https://posthog.com

PostHog is the only open-source Product OS, combining product analytics, session recordings, feature flags, cdp and a data warehouse in one.

We have a culture of written async communication (see our handbook [0]), lots of individual responsibility and an opportunity to make a huge impact. Being fully remote means we're able to create a team that is truly diverse. We're based all over the world, and the team includes former YC founders, CTOs turned developers and recent grads.

To apply see https://posthog.com/careers or email us [email protected]

[0] https://posthog.com/handbook/

There seems to be posthog.com analytics and AB or feature flag functionality that is blocked by adblockers. Probably that?