openreplay VS ClickHouse

Uncover frustrations, understand bugs and fix slowdowns like never before with OpenReplay — an open-source session replay tool for developers. Self-host it in minutes, and have complete control over your customer data. Check our GitHub repo and join the thousands of developers in our community.

- Optimize user experience: use insights to refine and improve your app’s usability.

Interested? For more details, you can check out the GitHub repo [0] or documentation [1]:

[0] https://github.com/openreplay/openreplay or documentation

[1] https://docs.openreplay.com/en/rn-sdk/

Hey HN,

For anyone who uses session replay tools to debug, monitor, or analyze user journeys, this feature might come in handy. OpenReplay — the self-hosted session replay tool that helps developers troubleshoot web apps faster — now supports tabbed browsing.

*Here's how:*

1. Capture and replay user sessions that span across multiple browser tabs, all within a single recording.

2. OpenReplay's tracker communicates across browser tabs, ensuring accurate tracking of each tab, even when duplicated or opened with `window.open` without `_blank`.

3. With "co-browsing", you can watch and support users in real-time and see how they navigate across multiple tabs of your app.

*Why it’s important?*

1. This feature is convenient for developers as it allows them to easily identify bugs by reviewing a complete session in one replay, rather than having to reference multiple recordings.

2. It provides a deeper understanding of the user journey and interactions across multiple tabs in your web app, helping in the comprehension of complex user behaviors and paths.

3. It provides accurate feedback on user tab actions such as opening, switching, and closing tabs, assisting in UX/UI improvements.

Interested? For more details, you can check out the GitHub repo at https://github.com/openreplay/openreplay.

You could maybe get in a scenario where a company rather sneakily changes their license without proper announcement to make usage non-open and billable, but that's pretty rare and bad behavior and that underhandedness may bite them back if it goes to court (I am not a lawyer). That said, it can happen. As an example, see this discussion I opened where the project switched licenses and the maintainers thought it was enough to only really announce this within a 1 hour YouTube video (Rather than their blog or update notes).

OpenReplay would not be typically be considered open source. (Which I have raised with them and have since been blocked from their repos).

How does it compare to OpenReplay ?

> Before deciding on ClickHouse, we were planning to use OpenSearch

You should have tried Quickwit :)

Anyway, sounds like a great project, best of luck!

[1] https://github.com/openreplay/openreplay

[2] https://github.com/quickwit-oss/quickwit

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;