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Shopify
identity_cache
Ruby2013–2020
Shopify / identity_cache

identity_cache

IdentityCache is a blob level caching solution to plug into Active Record. Don't #find, #fetch!

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5Distinct people
5Mentions
0Explicit recommenders
2KGitHub stars
REPOSITORY AT A GLANCE

What to know before exploring

What it is

IdentityCache is a blob level caching solution to plug into Active Record. Don't #find, #fetch!

GitHub

Where it is used

No documented product use has been verified yet.

What people are saying

No recommendation phrase was found in the indexed comments.

No classified warning is attached to this page. Read the discussions before treating silence as approval.

Also in these discussions

No other repository is repeatedly linked in the same discussions.

This week on Hacker News

Nov 7–Nov 14 UTC · Direct repository links and separately labeled related project stories. Indexed through 11/14/2026, 12:54:37 PM UTC.

No direct repository links were found in the indexed HN discussions over the past seven days. Older discussions are available below.

Mentions over time

HN mentions by year5 dated mentions

Observed mentions: 2013-03-07 14:26:53 UTC to 2020-09-17 16:04:09 UTC.

0122013-01-01 00:00:00 UTC to 2014-01-01 00:00:00 UTC (exclusive): 2 mentions; 1 submissions, 1 comments20132014-01-01 00:00:00 UTC to 2015-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2015-01-01 00:00:00 UTC to 2016-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2016-01-01 00:00:00 UTC to 2017-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments20162017-01-01 00:00:00 UTC to 2018-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2018-01-01 00:00:00 UTC to 2019-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2019-01-01 00:00:00 UTC to 2020-01-01 00:00:00 UTC (exclusive): 0 mentions; 0 submissions, 0 comments2020-01-01 00:00:00 UTC to 2021-01-01 00:00:00 UTC (exclusive): 1 mentions; 0 submissions, 1 comments2020

Counts come from the repository’s dated source evidence. Index cutoff: 2026-11-02 08:16:59 UTC.

View mention counts and date ranges
UTC ranges include their start and exclude their end. Select a period to filter the source evidence.
PeriodStart (UTC)End (exclusive, UTC)MentionsSubmissionsComments
20132013-01-01 00:00:00 UTC2014-01-01 00:00:00 UTC211
20142014-01-01 00:00:00 UTC2015-01-01 00:00:00 UTC000
20152015-01-01 00:00:00 UTC2016-01-01 00:00:00 UTC000
20162016-01-01 00:00:00 UTC2017-01-01 00:00:00 UTC101
20172017-01-01 00:00:00 UTC2018-01-01 00:00:00 UTC101
20182018-01-01 00:00:00 UTC2019-01-01 00:00:00 UTC000
20192019-01-01 00:00:00 UTC2020-01-01 00:00:00 UTC000
20202020-01-01 00:00:00 UTC2021-01-01 00:00:00 UTC101

What Hacker News says

5 sources
exterm·Sep 17, 2020
The answer to that question could probably fill another blog post :D Long story short, Rails and dependency inversion equals lots of friction. The whole framework is built on the assumption that it's OK to access everything from everywhere, and over the years we've built lots of tooling on top of those assumptions. E.g. we heavily use https://github.com/Shopify/identity_cache with active record associations that cross component boundaries. We also have a GraphQL implementation that is pretty closely coupled to the active record layer and _really_ wants to reach into all the components directly. All of those problems can be overcome, but this is definitely an area where we have to working against "established" Rails culture, and our own assumptions from the past.
In Under Deconstruction: The State of Shopify’s Monolith
1as·Nov 25, 2017
Yes. Rails has by now certainly crossed into boring software territory – arguably a [positive thing](http://mcfunley.com/choose-boring-technology) anyway – but it remains an excellent choice coming into 2018: - Out of the box, Rails has close to unbeatable developer ergonomics, tooling, stability, and ease of use - Lots of high quality, large companies use it (GitHub, Shopify, Airbnb, Square, Twitch) and have by now figured out how to scale it, often sharing and open sourcing their efforts, e.g. https://github.com/Shopify/identity_cache - If your product front end is simple, Turbolinks can be an excellent choice (find me a faster, more bug free product than Basecamp) - If you prefer to use a more modern JavaScript solution on the front end like Ember or React, Rails API is a perfect fit - The Ruby ecosystem and community are both very hig
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h quality
In Ask HN: Is Ruby on Rails still worth it?
hbrundage·Oct 24, 2016
> then you will have to do these optimizations yourself For the optimizations you listed they actually all still apply with a custom theme. The author doesn't have to do anything. Shopify caches all generated HTML, serves all assets from a CDN, and controls expiry without using TTLs because we know when anything changes. The stuff custom theme authors do have to do is things like bloat reduction / post-first-paint behaviour addition / css pruning etc etc. We're considering shipping mod_pagespeed for all customers too which would help automate a bunch of this stuff. > how do you handle sudden load spikes in the database Most of our read load is served by a datablob caching layer[1] so the DB is doing mostly stuff only it can do, writes, and we then have a carefully tuned schema that allows for massive throughput. We also buy really expensi
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ve databases -- we just took shipment of over a ton of database hardware in one datacenter in preparation for Cyber Monday. If we do hit our limit, we're able to throttle the number of people in the checkout while maintaining a good experience for customers. > Do you reshard and migrate data in real-time Yes > How does Shopify scale the application tier We shard by shop and build failure domains called pods that are self contained versions of each piece of Shopify that can failover independently between infrastructures. > How can tenants run scalable custom backend code Using Shopify Scripts. They're only available in the domain of carts and checkouts right now, but are rolling out to all our backend domain models in time. See https://help.shopify.com/api/tutorials/shopify-scripts > What happens if a database or server node crashes? We have automated failover in place at almost every level of the system, so unless we've screwed up somewhere, no one notices! > they can for example easily build a React/Angular single page applications, run server-side JavaScript code, do custom queries, build a native app around the same business logic and APIs, subscribe to websocket-based change streams etc Did the Thinks store end up using any of these features of the platform? I am sure lots of apps need these things, but for web storefronts a lot of this seems like overkill. Shopify also supercharges you when you want to move beyond just a web storefront: we have a mobile SDK for building native apps, connectors to let you sell on Amazon, Facebook, and anywhere you can inject HTML, a world class mobile administration app, a POS solution, a massive app store for other integrations, etc etc etc. > this is usually not an indicator for scalability and a low-latency design Again, sub 100ms response time and an order of magnitude more traffic every minute than the peak the Thinks sale saw... that's pretty good! I'm trying to get at the fact that building a web store from scratch, be it with a handy backend as a service or not, is going to be really hard in comparison to using Shopify. You sacrifice some small amount of flexibility, but you gain so so so much more by buying into the ecosystem. I still think it is unwise to try to compete with other platforms who's core competency is commerce. 1: https://github.com/shopify/identity_cache
In Building a Shop with Sub-Second Page Loads: Lessons Learned

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