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Excited about a stable C++ API for extensions!

I made a dry run extension a few months ago (https://github.com/aleda145/duckdb-dryrun), will be so nice to build it just once and know that it will always work.

Also urge anyone to make an extension, the template makes it quite smooth: https://github.com/duckdb/extension-template


Hard disagree. Sure their docs are bad, and it's sometimes buggy. But to me cloudflare is actually innovating and trying to offer "new" infrastructure. Durable objects and workers are super cool. R2 has free egress, isn't it insane that they could pull that off?

If what you want is a VM to run postgres then there are other offerings that would be much better.

Not saying they aren't evil though, they probably are, but the infra stuff is cool.


I disagree with your disagreement. I wrote the post and I am not blaming the innovation. I am blaming the chaos of innovation. Everything feels DISJOINTED.

The innovation is useful, the delivery of the innovation is the pitfall here.


Innovation is only linear in hindsight . Pure speculation on my part but once CF made some leaps in a particular area this enabled them to gather more data and shift direction to reach their over all goals by stifling the causes and the innovation that lead them there. New management comes in, requirements change and this is evident to us on the outside as disjointed behaviour. Companies need to make money from the internet for it to exist. Companies also need to behave and refrain from tragedy of the commons for the internet to keep existing as we know it.

They have cool tech but they can't do product, like most of big tech.

Have you tried wrangler? holy

Hire enough product owners and that's what happens.

That's why they need to buy startups every once and then, to bring some good bacteria in their messed up corporate gut.


yep, wrangler is a monster, the idea is solid - it's like the gcloud or heroku toolbet - the execution isn't nearly as neat.

This stance is a breath of fresh air. In my experience change management is the first thing to slap on when a bad release happens.

I've worked at a large enterprise that have a "Change Advisory Board", that you need to convince when you want to bump the major version on your linter. It has the effect of velocity slowing down to a crawl. Changes have to large, since otherwise it wouldn't be approved by the CAB. A slow mess.

At my current place we have to loudly declare "I CONFIRM COMPLIANCE" in every PR description. I'm not sure that anyone knows why, but it keeps the bureaucrats happy. Shrug


> that you need to convince when you want to bump the major version on your linter

I had to fight this at my last company. Some engineer not on my team thought "my team" should gatekeep all upgrades (including the linter). I gave a good faith response as to why that was a bad idea. It got implemented anyways. Despite saying that it should be "my team"'s responsibility on the proposal, the review board ended up being a random smattering of people. After a few months of them going "why am I a mandatory approver here?", it got reversed.

Compliance procedures for compliance sake.


My favorite thing about CABing things that shouldn't be CABd is that it then bunches up changes that all happen at the same time... after the CAB meeting. Now if something breaks, it could be any of the dozens of things that just got pushed in the 15 minutes after the meeting.

A declaration of fault from the executives' perspective if anything goes wrong

10 years ago I rode my bicycle from Connecticut to Central America. I stayed in Antigua for a few days to just relax and reflect. Thanks for bringing those memories back!

That is quite the ride! You're welcome, glad to hear it brought back positive memories.

Working on open sourcing my data analytics canvas: https://kavla.dev/

I've worked on it for about a year, with 1700 commits. I've been going back and forth if I should just open up the canvas or also the multiplayer experience.

I've always had the dream to make some money from a side project, but I don't think this one is it, so I'll just make the entire repo public. Just want to clean up some stuff first.

Lots of fun tech used: duckDB WASM, Cloudflare Durable Objects, tldraw and pocketbase


The landing page is teasing. Then I clicked 'Open a Canvas', expecting to play around with a canvas to understand the tool. But bummer, a login screen. Maybe you can let people try before making an account?

100% agree, it's on the todo list!

If you just want to see what it looks like here's a demo looking at hackernews data: https://kavla.dev/hn

There's also no email verification gatekeeping it so feel free to just input some bogus data when signing up


Ah, that's very cool. Thanks for the link. Fun to see other HN folks on the same canvas!

I'm very impressed how well durable objects work for multiplayer experience!

Also looks like the table shapes broke, there should be data that you can browse and download. I've replaced those with screenshots just in case anyone else sees it


That’s cool. Love the infinite canvas and multiuser aspect brought to data analytics!

I concur with the author. Personally I think I just won't read fiction produced after 2023. There's so much good literature already produced, why bother with the new stuff?

I feel very sorry to any budding new authors. Maybe we are entering a literary dark age?


To be fair, reading new fiction is… Well, it is not a waste of time, but you really need a good recommendation from another reader you trust to find the gems in the manure pile. I don’t know how much of ”booktok” and whatnot is just cynical marketing and how much of all this ”romantacy” or whatever is generated by LLM’s, but it might as well be. And same goes to literature awards, oh boy are some of those award-winning books trash.

But the thing is, bad art dissappears. People simply forget, because bad art just is not interesting. Maybe it has a nostalgia comeback or two, but eventually it just dies away with the people who made it, who sold it and who read/experienced it. The great art stays, because it is found again and again by yet another generation. I heard kids have somehow found Count of Monte Cristo again. They are still making movies of Homeros’ texts. Joyce never went out of fashion, neither did Shakespeare, Rabelais, Cervantes nor Proust.

So only thing you need to do is wait, really. Meanwhile there is more classic’s around no-one reads in a lifetime.


I'm interested in why you feel like this. Do you take this action because you can't trust traditional channels (blogs, established tradpub authors, Goodreads et al) to self-curate LLM writing out of the pool of available literature you would normally be aware of?

Yeah I think it boils down to trust issues. I can't know how the text was created. Anything created before 2023 I know that at least a human had to invest a significant amount of time to produce the story.

Maybe I'm a bit too reactionary though. Thinking about it some more I would absolutely read something if it was recommended by a trusted source (which in my case is almost always a human I know in the physical world).


I get the sentiment completely. I am actually doing what you're thinking: if it didn't come from my List Of People Who Know Of What They Speak I want nothing to do with it.

We really have gone full circle! It's quite upsetting.


I am afraid a lot of non-fiction is also AI generated slop...

"Hey ChatGPT here is a checklist of some facts, here are some sources, write a text about this"

Ultimately resulting in the same boring writing style over and over again for non-fiction.

Personally I enjoy the personal note in non-fiction. Political Girl by Maria Aljochina wouldn't be the same if it was produced by AI.


Why can't you just find authors you like and respect, that you trust not to write slop? Why go all cabin-in-the-woods about it?

Because there are also thousands (millions?) of such non-slop-books published before 2023?

You can't find new artists because art already exists? I feel like you're ignoring my question. It is not a good solution to "art is slop" to decouple yourself financially from all human artists. Your choice is making human art less sustainable.

Pretty clever to keep the existing parquet files as is (assuming daily partitioned) to not break any analytical queries. Also creating this index for the first time would make me sweat. With exabytes in the lake, the backfill bill will be $$$ (even just scanning the key column).

I'm not sure about the AI agent angle though, why would it need that specific context on a user level? I guess they are exploring a "chat with my spotify history" or user generated playlists?

(also the article has several LLM smells. It's technically interesting but reads like slop at times)


As a data engineering person I can say that this is a great write up!

Some thoughts:

A "bubbling" topic right now is conversational analytics (i.e. talk to your data). There has been an explosion of tools in the last 6 months. YC is backing one too: https://getnao.io/

I feel like pandas is also somewhat frowned upon, the industry has moved on from that. Most SQL tools can now do everything that we could only do with pandas.

In my network everyone is talking about DuckDB. As long as you are under a 1TB it will have everything you need. I think most people should start with that vs locking themselves into something like Snowflake


I love what I am hearing. I still see a lot of engineers using pandas, but it is such a horrible tools. You usually find an abandoned notebook with 100s of ”df_final_2” with sequential wrangling, making it impossible to understand what’s happening. Notebooks are also horrible for the same reason IMO.

With chat-your-data you have Hex, Claude + MCP, snowflake, Databricks etc… everyone’s in on it.


Just to add, people in my network have been talking about polars (as an alternative to pandas) and other dataframe libraries. They're much easier to use now thanks to the Narwhals compatibility layer (for example, Narwhals was recently added as a dependency to scikit-learn).


What's different between Narwhals and Ibis? Why does the former exist when the latter has already (struggled along) existing for a while? Narrower scope / benefit of hindsight? No support for "cloud" data frames like Ray and Spark?

Also Pandas is very much still a great tool and it's only getting better. It has some fundamental limitations that are relevant for processing bigger datasets or running things with higher performance. But it's still my preferred data frame for interactive day-to-day work. I only switch to Polars (or DuckDB) when I want to maximize performance.


There is a slide about Narwhals and Ibis here (a recording of a talk from PyData Berlin 2025): https://youtu.be/qOJiQtqI348?t=2496 TL;DR: It doesn't have to be Narwhals vs. Ibis because Narwhals supports Ibis.

Update: Here's a benchmark as well, but it may be outdated: https://www.kaggle.com/code/marcogorelli/narwhals-vs-ibis-ov...


I have never heard of Denodo before. "The only real semantic layer" is a bold claim. From the website it just looks like another data governance tool?


Got another daughter last week!

There were a lot of complications post delivery, and I want to make some sort of interactive story about it. We'll see how it goes

(Everyone is safe and sound)


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