The main limitation at the moment is that we only support a handful of Web APIs (e.g. `fetch`, `URL`, etc.) and NodeJS APIs (e.g. `readFile`), as well as QuickJS's built-in ES2020 APIs, so if you try to run an existing app you may find it needs a Web API we don't yet support. If so, please feel free to open an issue on the `spin-js-sdk` repo.
This resembles ascending a rope using prusiks, which is a lot of fun if you haven't tried it. Great to see a variation the helps people with limited mobility to get around unassisted.
I've been making my way through this book for the past few weeks; just started Chapter 20. I tried reading Harper's Practical Foundations for Programming Languages first, but it was too abstract for me, so I switched to TaPL.
What I like most about Pierce's book is that he introduces each concept with a formal, abstract definition, complete with proofs of correctness, but also follows that up with a concrete implementation in OCaml. The latter is very easy to follow if you've had some experience with the ML family of languages. I sometimes find myself skipping ahead to the OCaml version when I get lost in the math syntax, which for me is less familiar. I'm planning to come back to Harper's book later, but Pierce's book is the perfect fit for where I am now.
My only criticism is that some parts are very dated given it hasn't been updated in almost 20 years. In particular, the version of Java he discusses throughout the book (pre-generics, pre-type-inference) bears little resemblance to the modern one. And since 2002 we've seen affine types (e.g. Rust) start to have mainstream influence, among other things.
In case it's helpful, I'm compiling a list of resources as I learn type systems, logic, category theory, etc.:
I've implemented a RDBMS that supports this [1]. It handles joins, views (which are automatically materialized and incrementally updated), etc. It's memory only, and it doesn't support exotic stuff like recursive CTEs, but it does exactly what you're asking for. We used it in production successfully for frequently-updated real time data at the company where I used to work.
Notably, it uses persistent search trees such that each revision shares structure with the previous one, which makes diffing two closely-related revisions extremely efficient (just skip over any shared structure). Subscribers just receive a stream of diffs, with backpressure handled automatically by skipping over intermediate revisions. See [2] for a more detailed summary.
It also exposes revisions as first-class objects, which allows you to tag, diff, and even three-way merge them. Specifically, you can run arbitrary queries on both revisions and diffs. See [3] for examples.
It's no longer maintained, unfortunately. Someday I may revive it, perhaps adding support for spilling data that won't fit in memory to log-structured merge trees. I'd also rewrite it in a language like Rust, which will help flatten some of the more pointer-heavy data structures and reduce tail latencies. If anyone is interested in seeing that happen or helping out, let me know.
I'm really surprised this still isn't supported in mainstream DBMSes. The MVCC model in PostgreSQL seems particularly well suited to it.