Ex

Explaining GraphQL to a PM Through Analogy; Also: Encouraging Questions

Hacker News

Explaining GraphQL to a PM Through Analogy; Also: Encouraging Questions

Hey guys and gals, I just had a PM ask me a great honest and simple question and felt like posting my response here to A) encourage encouraging question asking. We're all imposters at some level and being honest about that will just help us all improve. B) See how you all can make my analogy better or more useful. Cheers! Text copied below since Notion requires login to read public pages now? wtf Notion bad job DO NOT ever say I have to promise not to laugh at you for asking a question! A) I commend ANY PM for their curiosity into ANY technical details B) Everyone pretends they know way more than they do in tech land so don’t sweat it C) I have trouble with some basic stuff like I mentioned in Standup like CSS. I just never learned it well SO, with that all said, a quick way to explain GraphQL It’s a technology created by a great team at Facebook that makes it more efficient for us folks on the front end to ask the backend for our data. Facebook the company blows but they do some cool stuff. This is one of those things Let’s use an analogy to explain GraphQL and compare it to what USED to be the standard - Rest APIs. With Rest APIs, we tell our backend team - “Hey, backend! Give us all of our users that have this ID” and the backend has to have already created something called an “endpoint” which is a simple URL you can plop into your browser and it shows you some data. For example: www.example.com/user/1 - if we go to this hypothetical endpoint, we expect that we will receive back ALL (SERIUOSLY - ALL OF THE data that the backend thinks is appropriate to hand us for that user. That’s fine, but it’s a huge waste. Imagine if you wanted to ask your friend what her address was, but instead of her responding with her address, she’d write down her birthday, her phone number, all of the people she knows, her social security number, her password for her phone, and a whole bunch of other useless stuff. You just CARE about what her address, but she provided you with a bunch of information that wasn’t at ALL what you cared about. The question becomes: How do we solve this with a URL the old way? Do we ask our backend to create a new “endpoint”? Something perhaps like www.example.com/user/1/address? That would work, but as we add more data to our user, our backend folks are going to have to create new endpoints for each one of the new pieces of data that we add, so we ignore this solution and instead just keep adding data to that first URL endpoint. This is the problem GraphQL solves. The frontend TELLS GraphQL what data we want about the user and it responds with only that data. The wastes WAY less bandwidth from the front end to the back end, speeds up our queries, and makes the code that provides data way more flexible. Probably a little more technical information than is warranted here, but the request ends up looking like below instead of some convoluted URL like www.example.com/user/1/address user { address } and that’s it! The backend will now respond ONLY with the data we want, which makes our responses much quicker and faster and that’s good for all parties involved, including our end users. Thanks for your question! Hopefully this helps you understand and please feel free to always ask questions. The more our PM folks know about the technology, the better! Props to you :clap:

Share card

Actual performance

2points
Did not reach leaderboard

Launch Intel predictions

Analyze your own launch →
Product HuntOn track for Day 1 leaderboard · Strong signals: user, new, code · Missing: mac, agents, macos
93%93% predicted probability of success on Product Hunt, based on ML models trained on real launch data.
best fitHighest predicted score across all platforms for this description.
Indie HackersFits the IH revenue-focused audience · Strong signals: created, ios, including · Missing: supports, reddit linkedin, podcasting
91%91% predicted probability of success on Indie Hackers, based on ML models trained on real launch data.
Hacker NewsStrong engagement from HN community · Strong signals: ide, io, including · Missing: https docs, excited, just released
68%68% predicted probability of success on Hacker News, based on ML models trained on real launch data.
nativeThis product was originally launched on this platform.
TrustMRRLess likely to generate early MRR · Strong signals: ios, users, way · Missing: mobile apps, personal, entrepreneurs
40%40% predicted probability of success on TrustMRR, based on ML models trained on real launch data.
AppSumoMay struggle as an AppSumo deal · Strong signals: efficient, users · Missing: plus, platform, intuitive
37%37% predicted probability of success on AppSumo, based on ML models trained on real launch data.
Acquire.comPre-revenue stage for this audience · Strong signals: arr · Missing: mrr, revenue, profit
13%13% predicted probability of success on Acquire.com, based on ML models trained on real launch data.
BetaListMay not resonate with beta-testers · Missing: web3, chat, crypto
0%0% predicted probability of success on BetaList, based on ML models trained on real launch data.

Incorrect prediction on native model

Similar products

My
My First Hackathon Project (TL/PM)55%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

My First Hackathon Project (TL/PM)

Hacker News1
Stare
Stare22%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

A guide for PM aspirants

Indie Hackers3communication
PM
PM Reports for FogBugz52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

PM Reports for FogBugz

Hacker News3
Or
Ora.pm: June Update52%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Ora.pm: June Update

Hacker News8
Ai
AirTask PM, manage projects effectively47%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

AirTask PM, manage projects effectively

Hacker News3
NoMBApm
NoMBApm12%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Stories about people transitioning to PM without MBA

Indie Hackers
Cleo
Cleo83%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

The AI PM that runs your team

Product Hunt+378Productivity
HeartBeat.pm
HeartBeat.pm22%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

app monitoring tool

Indie Hackerscommitment-full-time
A
A poem generator for Quora questions43%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

A poem generator for Quora questions

Hacker News1
Ri
Riter PM tool has announced its full support for startups57%Launch Intel prediction score: how likely this product is to succeed on its source platform, based on its name, tagline, and description.

Riter PM tool has announced its full support for startups

Hacker News1