hypercrud.browser

Philadelphia or remote - dustin.getz@hyperfiddle.net I co-made http://hyperfiddle.net/ which is JSFiddle for Datomic. Work history with screenshots: http://www.hyperfiddle-consulting.com/ We are world-class UI experts as demonstrated by our cutting-edge open source contributions to the React.js and Datomic ecosystems. Our bread-and-butter is full stack UI work with emphasis on functional programming and React.js, though obviously we can handle anything, emerging languages etc, the crazier the better. We also enjoy reasoning about distributed systems and scale. Clojure, ClojureScript, Javascript, React.js, Scala, Java https://github.com/hyperfiddle/hypercrud.browser https://github.com/jsdevkr/react-chatview https://github.com/dustingetz/wingspan-forms https://github.com/dustingetz/react-cursor

SEEKING WORK - remote or Philadelphia - dustin.getz@hyperfiddle.net I co-made http://hyperfiddle.net/ which is JSFiddle for Datomic. Work history with screenshots: http://www.hyperfiddle-consulting.com/ We are world-class UI experts as demonstrated by our cutting-edge open source contributions to the React.js and Datomic ecosystems. Our bread-and-butter is full stack UI work with emphasis on functional programming and React.js, though obviously we can handle anything, emerging languages etc, the crazier the better. We also enjoy reasoning about distributed systems and scale. Clojure, ClojureScript, Javascript, React.js, Scala, Java https://github.com/hyperfiddle/hypercrud.browser https://github.com/jsdevkr/react-chatview https://github.com/dustingetz/wingspan-forms https://github.com/dustingetz/react-cursor

ACID's C is about the write side: "ACID is a set of properties of database transactions" (wikipedia) which is different than CAP's C: https://en.wikipedia.org/wiki/Consistency_(database_systems)... Postgresql with read replicas is ACID-Consistent transactions because single writer, and CAP-AP eventually consistent because distributed reads. It is easy to agree with you here: "PostgreSQL basically stops working well too, once you start mixing transaction processing and business reporting and BI in the same box at scale." It's worse than that - the app has to be coded before it can be scaled so you get fucked by complexity-scale via ORM a lot sooner than bigdata-scale. But as you sort of say, the point of a data warehouse is to be cap-AP (eventually consistent) through read-replicas without breaking ACID-consistent transactions for the syst

JOIN tables, sparse tables, deeply nested JOINs - all this is needed to code link-following in the relational model. So you need an ORM to handle the JOIN pain for you, but relational db query perf degrades as your joins get deeper, so the ORM needs to make hard choices around caching and database query round tips - but the ORM doesn't have enough information about the UI to make these choices - you end up needing to code the app logic into the ORM via caching and query optimizations. And now you're writing code, that's not links and forms anymore. At ClojureNYC last night I gave a talk about literally this! Here are the slides: https://github.com/hyperfiddle/hypercrud.browser/issues/4

My project is a bit of a spiritual successor to HyperCard: https://github.com/hyperfiddle/hypercrud.browser