toastdriven

Partially due to familiarity, partially due to other projects. Django will be handling the standard webapp things (registration, serving archives, etc). To be clear, there will be a lot of plain Python code handling the other aspects, with a goal being that you could relatively easily replace the Django parts with your favorite tech stack (say Flask or Tornado). Smaller parts making a greater whole.

That's in the video (~1m0s mark). The prototype is present, but ugly/unfinished. We could put it up publicly, but it wouldn't represent the final product anyhow.

Sounds interesting, though I wouldn't trust MongoDB with my (or anyone else's) data.

The problem is that, while building the core of this is easy-ish, the end result should be something very complete & easy to stand up. Our prototype functions (barely, mostly just due to a lack of time), but it's not polished or complete. It's not smooth, easy to use/administer & it doesn't include all the little details that go into successful software projects.

Perhaps I'm mistaken, but I see it more as crowd-funding (I feel dirty using that term) a useful service with the added benefit of being able to run it yourself. The goal was to spur more/better discussions (than what private chat or crappy forums currently do).

We could certainly open up the code sooner, it just won't be polished enough to use from the get-go.

Most of all, it's an experiment for us. Do other people want this service as much as we do? Is this a valid way to try to bootstrap something? Can a service 100% (K, so 95%) open-source itself & still make ends meet?

Understandable. For us, if it were just a library or an extraction, we wouldn't be trying to fund it. However, what we're trying to build is more like an open-source product, essentially an entire service made public so anyone can use it.

Because of the time commitment involved, we're trying to fund it so we can work on it (as well as the software we'll be building on top of) full-time from the start.

Using it to power the activity stream of a small site (+ Postgres & Redis). <3

We do most of our development in Django, so Postgres is a natural fit. Every tool has its sweet spots, so you should use the tool that best fits the task.

For instance, Postgres is great for highly structured data (say, photos on a website). Riak shines when your data flexs more & you have a lot of it (say an activity stream).

I was tempted to do some comparison, especially to Couch/Mongo/Cassandra, but ran out of time. I'll consider a follow up that compares them.

In short, Riak wins out to me against all three:

* Faster than Couch & easier clustering * Better data integrity than Mongo * Less conceptual overhead & simpler code than Cassandra