HATEOAS, REST, and the quest for a general hypermedia client 2017

The whole point of REST archiecture is to enable a general hypermedia client. But REST is slow!!! General purpose graph navigation by link following means client/server round trips for each link followed. I like to call this, REST's "subresource problem." To solve the subresource problem efficiently, Hyperfiddle makes some very unusual architecture choices.

Hyperfiddle vs GraphQL (notes on Lacina launch post) 2017

Comparison of Hyperfiddle with Walmart's Lacina, a GraphQL impl for Clojure

Great products take things away - Joel Spolsky 2017

The most elegant hack is when somebody says, These 2000 lines of code end up doing the same thing as those 2 lines of code would do. I know it seems complicated, but arithmetically it’s really the same.

Network effects 2017

This is a collection of discussion about network effects.

Datomic vs the O/R Impedance Mismatch 2016

Datomic's key insight is that the Object/Relational Impedance Mismatch is the source of non-essential complexity in CRUD apps, and that immutability in the database permits a solution.

UI State: Graph vs Tree 2016

Around 2015/16, the state of art UI thinkers began to explore backing UIs by graph-like state rather than immutable tree-like state. This is a very rough sketch about this and how it relates to the design of Hypercrud.

ΔUI :: Δstate -> ΔHTML; UI = reduce(ΔUI, Δstates) 2017

Brain dump about UI rendering performance state of art in 2016.

The problem with REST - Pete Hunt 2017

"The problem [with REST] is when you want to fetch data in repeated rounds, or when you want to fetch data that isn't expressed well as a hierarchy. Think a graph with cycles -- not uncommon"

Hyperfiddle vs hackers 2017

Hyperfiddle changes the balance of power between offense and defense.

Datomic Conf: What Datomic does to REST 2015

This 10min talk about why Datomic is a basis for solving the problems of REST, which are essentially complex data-fetching costs to display readonly data on a page. Getting rid of read complexity is the whole point of Datomic.

Michael Gaare on Datomic storage implementation 2017

Datomic Pro's code/data locality model assumes perfect caching which works out "because immutability" (major handwaving). To make this work out, Datomic Pro makes some very specific tradeoffs wrt indexes and storage implementation, and at scale this abstraction does leak, which is why Datomic makes us give hints in the form of storage partitions.

Datomic and CAP theorem 2017

Datomic is strongly consistent and linearizable, like git. In researching this I learned that CAP is no longer an effective razor.

Michael Gaare on the semantic web and Datomic 2017

MICHAEL GAARE: My observation is that there's a fundamental, philosophical problem. Semantic web has essentially Platonic underpinnings. There's some perfect description of the world, "universal truths" as one guy I worked with would put it, and we "merely" have to describe our data in those terms. That flies in the face of everything we as engineers have come to understand about how people, processes, and language works.

Datomic – what is it and why should I care? 2018

I get asked this a lot so I wills tart collecting quotes and stuff here.

Why do apps have to be async in the first place? 2017

Our async abstractions have ways to propagate the error through our asynchronous pipeline, and like, that’s okay, but what if we could make it not fail in the first place? What if we could make failure impossible?

Is Datomic strictly better than Facebook's graph datastore? 2017

This post compares Datomic (today, 2017, post-Datomic Cloud announcement) to Facebook's graph datastore as described in 2013. They are almost the same, except TAO is a triple store & eventually consistent; Datomic is a 5-store and strongly consistent. Contrary to popular belief, Datomic's single-writer-per-database ACID is exactly the same as Facebook's single-writer-per-shard, so I think Datomic Cloud can absolutely scale up to to Facebook-sized write loads, and then beyond due to immutability.

Datomic FAQ 2017

Short questions answered from slack and reddit

Datomic solves reference traversal in databases 2017

I think there is a deep reason for the success of Mongo, which is no-friction reference traversal. Reference traversal is the killer feature that programmers instinctively reach for in the database, because references are deeply baked into modern programming languages, references is how we think.

Immutable HTTP representations 2017

HTTP caching is annoying, here is a collection of useful links and notes, specifically about Datomic and Hyperfiddle immutable data-oriented architecture which has some interesting opportunities for "correct" caching.

Michael Gaare on Triple Stores 2017

"Among other reasons, I think they failed because they suck at writes. Like relational databases, they're "place" oriented."

HTML popovers without javascript 2017

I think this is possible to do, here are some notes

Does Datomic have location queries? 2017

Code/data locality means "you would just build an in-memory specialized data structure prior to querying, then pass it as a parameter of your Datalog query and call it using regular function calls."