NextCloudPi VS readyset

nextcloudpi.com

It works great and is reasonably fast if you connect it over ethernet. If you have a newer firmware, which has already enabled the boot from SSD on your pi it is super easy (otherwise just Google how to set up boot from ssd with a microSD). Afterwards you can use the raspberry pi flashing tool to flash the image of nextcloudpi on your ssd. This includes the 64bit raspberry pi OS, a running Nextcloud instance and some other handy tools (like help to set up security features). The first setup can be done with the IP adress of your Pi in an internet browser of a device in your network. Here is the link to the image of NextcloudPi https://github.com/nextcloud/nextcloudpi

Issue 2 still persists and after digging around found this issue reported on git https://github.com/nextcloud/nextcloudpi/issues/1752 but cant figure out how to sort it

Install nextcloudpi (https://github.com/nextcloud/nextcloudpi) Install Nextcloud app on your phone.

If you want to update faster than the docker image is published, you'll have to build the image locally: https://github.com/nextcloud/nextcloudpi

My best experience in out of the box comes from Nextcloudpi: https://nextcloudpi.com/

Nextcloud is functionally similar to Dropbox, Office 365 or Google Drive but is self-hosted so you are in control of your data. This version is a lightly-forked version of NextCloudPi, which was developed for SBCs like the Raspberry Pi. Only a few changes from upstream and some SysV initscripts were required to get this working nicely in Linux Deploy.

Since cache consistency is a complex research space with things like https://readyset.io/ and https://www.usenix.org/system/files/conference/nsdi13/nsdi13... it would be great to hear more specifics about what this is giving up in order to sidestep all that complexity.

I also faced similar issues and was looking for easy ways to improve performance in our application when I came across an awesome tool called Readyset. It sits between your application and database, intelligently caching complex queries while automatically handling invalidation. This setup can significantly boost performance without requiring major changes to your existing infrastructure.

- Some platforms like Supabase Realtime [3] and Firebase offer subscription models to database changes, but these solutions fall short when dealing with complex queries involving joins or group-bys.

My vision is that the modern frontend to behave like a series of materialized views that dynamically update as the underlying data changes. Current state management libraries handle state trees well but don't seamlessly integrate with relational or graph-like database structures.

The only thing I can think of is to implement it by myself, which sounds like a big PITA.

Anything goes, Brainstorm with me. Is it causing you headaches as well? Are you familiar with an efficient solution? how are you all tackling it?

[1] https://readyset.io/

Postgresql + MySQL Cache https://github.com/readysettech/readyset

I just wanted to give a high five for having Jepsen tests for this: https://github.com/readysettech/readyset/tree/stable-240117/...

This example is a great use case for partial incremental view maintenance systems like ReadySet: you automatically get something like the “prepopulating the cache” section (toward the end of the blog) while only caching the data the application is using, and avoiding the need to manually implement any sort of invalidation logic.

(Disclaimer: I used to work for them, but don’t anymore. It’s all available for free on GitHub though for anyone interested: https://github.com/readysettech/readyset)

There are systems that will do that for you like https://readyset.io/.

ReadySet

readyset.io is the company that jonhoo was associated with for work on noria

Might be interesting to try out https://readyset.io for this use case.