augustl

Love to hear stories and real-world experience like this shared! I feel us tech folks should start Facebook groups similar to those "Old Photos from <city I grew up in>", except photos and stories from tech :)

I was a huge N9 fanboy. Wish I didn't sell mine, and that Microsoft didn't kill it :)

Happy 9950X user here. Super happy with it, everything is crazy fast. Not a gamer, according to internet and benchmarks the extra cost is only worth it for gaming workloads.

I use Arch, btw ;)

Kotlin is a much better Java so that's what we use :)

I have a friend who maintains a gazillion JVM based apps for the Norwegian tax authorities and he's a Kotlin skeptic. He's pretty tired of maintaining and porting various small apps and microservices from arcane old and discarded Scala web frameworks etc. Given how locked-in Kotlin is to a single company, I kind of get his skepticism.

With TOTP you have a private key that you don't transmit over the wire, as opposed to your password, so security is improved even though the password and TOTP is in the same vault.

Jepsen is awesome, on so many levels!

> Without deep pockets for high-RAM servers

I just got a dedicated server on Hetzner to test out some things. It's $70/month with 64gb RAM and a CPU that builds a complex C++ thingie in 11 minutes where my laptop spends about an hour :D

Scaling is of course not trivial, but the same set of backoffice apps I've worked with throughout the years that would be a good fit for Datomic, has a working set for the database much smaller than 64GB.

> they seem like niche features

That's the thing, though. Maybe it's because I've use Datomic a bunch. When I'm on projects that use a SQL db, a handful of problems are just fundamentally solved in Datomic, and none of the super knowledgeable devs that know SQL in and out are even aware that they are problems.

Some examples:

- What caused this column of this row to end up with this value?

- Oh no, we were down 3am but when the first person investigated it at 7am (oh those backoffice SLAs...) everything works fine and nobody knows that the db state was at 3am

- When we wrote value X, what other values did we also write at the same time?

- We need to carefully write a transaction that reads some data, writes some data, and reads some more data, and hopefully lock correctly, and hopefully we understood the isolation level (that we probably didn't set anyway) correctly and...

Which makes me think I must be the crazy one...

> I still think there’s elements of an amazing product here

Interesting framing. The people behind Clojure and Datomic aren't known for being amazing at scaling and shipping products (i.e. marketing and all that jazz).

This is also not me judging them for it, I haven't built and shipped a Datomic, much less marketed it.

Yes - if I understand you correctly :) Datomic writes opaque blobs of index data to existing storage, such as Postgres or dynamodb or a handful of others. But you can't query that data meaningfully directly, it's just a bunch of compressed datomic-specific index data in there, no domain structure or query power etc.

I've used Datomic from both Kotin and Groovy (!)

I presented on Datomic at KotlinConf too, with some live coding starting around the 31 minute mark https://www.youtube.com/watch?v=hicQvxdKvnc

You probably need to be on the JVM, as the peer library (i.e. the "good one", where you embed the full query engine and data fetching directly into your business logic) is so far only implemented for the JVM.

I suppose 10+ years of weird license models and a hefty price tag haven't helped. Datomic turned free (but still proprietary) in 2023 though. But why Datomic isn't more widely adopted is a huge mystery to me...

It's free now - but I suppose 10+ years of being both closed source and paid didn't do wonders for adoption.

What part needs a cluster in your experience? The Datomic deployments I've been involved with have been running on a single server, with a single instance of backing storage etc.

Datalog is interesting indeed... Back when I first started using Datomic in 2012 I had just fundamentally decided to use it, and it took probably a week before the query language "clicked", i.e. to be able to actually compose my own queries and not just copy paste my way to something that works.

Statistically (and from experience) I'm probably the weird one here, but I cannot fathom why Datomic isn't more popular.

I get that postgres is a good default in many cases, and I don't expect SQL to die tomorrow. But there are _so many_ apps (most/all backoffice apps I've worked on for example) with 10s or 100s of transactions per second at most, that would love to have the data available directly inside your business logic, and where both business logic and devops would improve by many orders of magnitude by having a full transaction log of all changes done to your data over time.

Is it _just_ because Datomic is different and people don't get it, and that preconceived notions makes you think Datomic is something it isn't?

Here's to the crazy ones!

Predictions and pre vs post accident is an interesting subject.

Which bridge that is currently in operation should be closed next?

(Not a dunk on the article, which brilliantly addresses the difficulty of knowing in advance vs making real world changes. Practical Engineering is an awesome YouTube channel!)

FWIW, I recently used Wordpress as a headless CMS, with a Next.js frontend that gets pinged by webhooks from wordpress to invalidate caches etc. I haven't really found any headless CMS that's easier than wordpress for non-technical users to post content. And I get to write the front-end in Next.js so I get to skip most of the plugin shenanigans in WP :)

And apparently the effect is much more jarring in VR - which is why Valve solved it for Half Life: Alyx

https://www.youtube.com/watch?v=h_MuWmYKGIc

I hope we get bootcamp on Apple silicon, so we can see if it's the hardware or the OS that's causing most of the trouble :D

Good to know! I almost wonder if my specific laptop is broken in some way. Either that, or I'm overly sensitive to these things. And the Venn diagram overlap of people who often use both macOS and Windows is probably not that large... :) I don't see many people talking about this!

After switching from an 11th gen Intel Dell XPS, to a M1 Macbook, I resist returning to PC laptops (even though I prefer Windows) until someone confirms that newer Ryzen and Intel chips are comparable in terms of "perceived performance" to Apple silicon. The whole laptop simply becomes syrupy on battery. Even if I go high performance mode in Windows settings, the whole device is just so laggy compared to a Macbook. And, in high performance mode, the laptop has probably at _most_ 2 hours of battery life in it.

Has this improved since 11th gen Intel?

I would love to see analysis on the trade offs with KYC and AML. How much does it actually help in fighting crime? Vs. all of the lost opportunities due to all of the red tape and regulatory blockers for legitimate business models.

No wonder Apple has been adamant in keeping 3rd party devs away from executable memory :)

This is probably a dumb comment, but have you looked into using WSLg? I.e. also run the GUI inside WSL? The integration between Win and WSLg is pretty seamless!

I'm not sure if I even trust Intel/Windows at this point. The m1 macs are just so much snappier in absolutely every way imaginable than my old 11th gen Dell. My old PC would some times take minutes (!) to fully wake up from sleep, the battery drained in a couple of hours when coding, and it was sluggish the whole time compared to plugged in performance. I plan to see if I can borrow someone's 13th gen PC and use it for a week and see how it compares. I'm not able to find any reviews that covers the user experience on and off wall power.

I have a similar relationship with gaming. BOTW and Dark Souls are my favorite games of all time, but I've never gotten around to finish them.

Interesting link, thanks for posting!

Datomic's covering indexes are heavily based on their built-in ordering, and doesn't really have much flexibility in different ways to sort and walk data.

Personally, I'm a fan of hybrid database approaches. In the world of serverless, I really enjoy the combo of DynamoDB and Elasticsearch, for example, where Dynamo handles everything that's performance critical, and Elasticsearch handles everything where dynamic queries (and ordering, and aggregation, and ....) is required. I've never done this with Datomic, but I'd imagine mirroring the "current" value of entities without historical data is relatively easy to set up.

Errata: (get response :headers)

I suppose I think of this the other way around. When the query engine is inside your app, the query engine doesn't need to do loop-like things. So you can have a much simpler querying language and mix it with plain code, kind of similar to how you don't need a templating language in React (and in Clojure when you use hiccup to represent HTML)

Additionally, this laziness means your business logic can dynamically choose which data to pull in based on results of queries, and you end up with running fewer queries as you'll never need to pull in extra data in one huge query in case business logic needs it.

Anecdotally, all the ones I've worked it where I've used SQL have needed it. I've always ended up wondering when, why and who changed an attribute to its current value, but that's not knowable unless you jump through hoops and manually implement it.

Fyi, Datomic lets you look at the entire database at any point in time, as an immutable value. Also, you can annotate transactions with metadata, and query for "which tx wrote this specific value for this row/column" and look at custom metadata you added to the tx to reason about your system. Doing all of that in SQL is not trivial, to say the least.

It depends! If you want to lazily walk data, you can read directly from the index (keep in mind, the index = the data = lives in your app), or use the index-pull API which is a bit more convenient.

However, if you want to paginate data that you need to sort first, and the data isn't sorted the way you want in the index, you have to read all of the data first, and then sort it. But this is also what a database server would need to do :)

In Clojure, response.headers is still data :) You just use the built-in ways of reading named keys, such as (:headers response) or (get headers :response).