Cool project! I wonder what commercial use cases come from it. On the My First Million podcast they talked a about a company selling color predictions to brands for multiple six figures. Maybe you can find correlations and predictions in the data one day.
We connected it with our Rails app (main reason was that we jse inertia-rails and React on the frontend).
With MUX you give it a URL to create videos. That doesn’t work with google drive, so we do some hacks in a background job and click download, then store it in activestorage. Then provide MUX with our url.
API and backend is good. Pricing also cheaper than S3 in most cases. We are not live yet, but it works reliably so far.
This. We started using it with Rails and it’s been great.
I do like scrappy rails views that can be assembled fast - but the React views our FE dev is putting on top of existing rails controllers have a much better UX.
The specs are great for 2025. Let’s wait for 2027 when BYD has a better performing model for much less.
I am all vouching for VW’s electric efforts. I drove the ID Buzz which is great. I just wonder if they could sell competitively without tariffs in the EU.
What they meant was https://github.com/oldmoe/litestack which has a lot of things built on top of sqlite, like job queue and caches. Rails 8 now comes with most of them out of the box.
My SaaS ran on litestack until rails 8 came out, then I switched without problems.
Yeah I used the full litestack (and litestream for backups) for my SaaS. Oldmoe is also auper helpful on twitter.
Once Rails 8 came out I switched it all over to the solid* gems which pretty much did the same thing.
Sqlite is awesome in the beginning, especially as there are no extra services to start (I only have a web process and a jobs process), all is sqlite.
Sometimes there are db locking issues (using blazer gem, so I guess that uses a different adapter), and I had to optimize some queries. But that’s about it. The SaaS processes thousands of job daily (mission control gem is awesome) and stable so far.
At one point our DB grew to 16GB because I stored all Api requests. Even then it was still fast (except queries on that api requests table).
Running four sqlites definitely saved me some time which I could use for customer focused things. Highly recommend for MVPs, probably more.
This works surprisingly well. Just shared it with my sci fi group.
Idea: make an email opt-in and then new releases based on old preferences. My use case is always to go to DVDs/netflix releases, filter for sci fi and then high IMDB.
Cool project! I wonder what commercial use cases come from it. On the My First Million podcast they talked a about a company selling color predictions to brands for multiple six figures. Maybe you can find correlations and predictions in the data one day.