ClickHouse VS Caddy

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;

No, look at the associated unit test: https://github.com/caddyserver/caddy/blob/c6eb186064091c79f4...

If that test fails we could serve PHP source code instead of having it be evaluated, a major security flaw.

However, it's very unlikely that .NET developers will directly expose their Kestrel-based web apps to the internet. Typically, we use other popular web servers like Nginx, Traefik, and Caddy to act as a reverse-proxy in front of Kestrel for various reasons:

I think that recompiling with upgraded Go will not solve the issue. It seems Caddy imports `golang.org/x/net/http2` and pins it to v0.22.0 which is vulnerable: https://github.com/caddyserver/caddy/issues/6219#issuecommen....

Caddy [1] is a single binary. It is not minimal, but the size difference is barely noticeable.

serve also comes to mind. If you have node installed, `npx serve .` does exactly that.

There are a few go projects that fit your description, none of them very popular, probably because they end up being a 20-line wrapper around http frameworks just like this one.

[1] https://caddyserver.com/

Each app’s front end is built with Qwik and uses Tailwind for styling. The server-side is powered by Qwik City (Qwik’s official meta-framework) and runs on Node.js hosted on a shared Linode VPS. The apps also use PM2 for process management and Caddy as a reverse proxy and SSL provisioner. The data is stored in a PostgreSQL database that also runs on a shared Linode VPS. The apps interact with the database using Drizzle, an Object-Relational Mapper (ORM) for JavaScript. The entire infrastructure for both apps is managed with Terraform using the Terraform Linode provider, which was new to me, but made provisioning and destroying infrastructure really fast and easy (once I learned how it all worked).

So I dug a little deeper and came across this gem: Caddy. Caddy is this fantastic, extensible, cross-platform, open-source web server that's written in Go. The best part? It comes with automatic HTTPS. It basically condenses all the work our scripts and manual maintenance were doing into just 4-5 lines of config. So, stick around and I'll walk you through how to set up an automatic SSL solution with Caddy, Docker and a Node.js server.

Let's use Caddy which can act as reverse-proxy with automatic HTTPS coverage.

Even if it may be simple, it doesn't handle edge cases such as https://github.com/caddyserver/caddy/issues/1632

I personally would make the trade off of taking on more complexity so that I can have extra compatibility.

One of the most heavily used Russian software projects on the internet https://www.nginx.com/blog/do-svidaniya-igor-thank-you-for-n... but it's only marginally more modern than Apache httpd.

In light of recently announced nginx memory-safety vulnerabilities I'd suggest migrating to Caddy https://caddyserver.com/