datascript VS relic

Hi pests, I don't think the criticism in the comments gives a full picture.

I wrote about a particular flavor of datalog, in common use today. [1] [2]. The earliest representation I know, which matches the syntax of my essay, was in SICP [3]

There's another, more academic form of datalog, which looks a lot more like prolog. Both have lots of similarities: both systems have a set of facts and rules. Both systems have can take a partially filled fact or rule, and find all matching facts. The more academic flavors of Datalog are useful for general logic, and particularly powerful for recursive questions. The variant I showed is more tailed for database queries.

[1] https://github.com/tonsky/datascript

There is also datascript as a similar option.

What's the use case for relic? Sounds similar to https://github.com/tonsky/datascript ?

This look nice !

Datascript seems to be another Datalog engine (in memory only)

https://github.com/tonsky/datascript

Inspired by past work: LINQ, inline-python, crepe, DataScript, Riffle.

An in-memory database like Datascript may be worth looking into. Otherwise you could take an indexing approach: put all the data into one big map indexed by some unique key, and have a bunch of supplementary indexes that are updated on insertion.

I've been tooling around with "Tuple Database", which claims to be FoundationDB for the frontend (by the original dev of Notion).

https://github.com/ccorcos/tuple-database/

I have found it conceptually similar to Relic or Datascript, but with strong preformance guarantees - something Relic considers a potential issue. It also solves the problem of using reactive queries to trigger things like popups and fullscreen requests, which must be run in the same event loop as user input.

https://github.com/wotbrew/relic

As an alternative to datascript you might be interested to try https://github.com/wotbrew/relic which does materialized views of queries with incremental maintenance.

I came across this after seeing relic[0] submitted the other day and thought it was pretty interesting.

I've been into CRDTs for a while and have started wondering about generic mechanisms for distributed data. This lead me to read a lot more about the Relational Model of data and eventually to the Event Calculus.

What's interesting to me is that these things end up feeling a lot like CRDTs[1] or Event Sourcing. I haven't quite finished pulling on these threads but the relic link was a timely read considering!

I really liked the first half of this paper and the Authors categorization of complexity. However the second half fell a bit short for me. It seems they made the same mistake as many other people (SQL != Relational) and their idea of Feeders and Observers seems a bit more like an escape hatch than an elegant method for interfacing with the outside would.

[0] https://github.com/wotbrew/relic

I have recently cut the first alpha release of relic that I'm happy to share: https://github.com/wotbrew/relic.