I did something that surprised myself. I always thought that people are right in saying that GraphQL breaks HTTP caching, but I never deeply analyzed if that's actually true because so many people say the same thing. So I analyzed this and many other claims and was surprised to find out that almost every claim comparing REST vs GraphQL is either wrong or misleading.
We need to stop calling N+1 a GraphQL problem when it's simply an API problem (and REST has it at the HTTP layer while GraphQL has it as the resolver layer, which is actually an advantage for GraphQL, but people typically picture it differently). Anyways, this post tries a scientific/research-driven approach in the hopes to combat the AI slop that makes bad claims about GraphQL.
GraphQL is a really powerful query language, Fragments are extremely powerful, and the ecosystem is very healthy with multiple vendors and developments like oneOf directive, defer, etc.
There are a lot of tools already that do local speech-to-text, but none of them allowed me to "select" code/text in a file and then paste a reference to my selected code together with the transcript.
I wanted this to work locally and I wanted it to work independently of the IDE (because I'm using multiple). I also wanted it to work with any coding agent (Claude, Codex, OpenCode).
So I put together parakeet & ripgrep in a Rust tauri app. It works perfectly for me and I'm using it every day whenever I'm coding. Maybe it's also useful for others.
One thing I find interesting is how GraphQL has evolved from an API technology for API consumers with "different needs" to an API technology for agents. What helped organizations scale GraphQL across multiple teams is Federation, a way to split one supergraph into multiple subgraphs. So, what works well to scale teams actually works equally well for agents. The core value you can get from Federation is a "coordination" layer that is deterministic. Now, what's interesting is that you can scale agentic software development pretty well when you have a deterministic layer where everyone involved can agree. I wrote more about this on our blog if anyone is interested: https://wundergraph.com/blog/graphql-api-layer-for-ai-agents
The problem with this article is that GraphQL has become much more an enterprise solution over the last few years than a non enterprise one. Even though the general public opinion of X and HN seems to be that GraphQL has negative ROI, it's actually growing strongly in the enterprise API management segment.
GraphQL, in combination with GraphQL has become the new standard for orchestrating Microservices APIs and the development of AI and LLMs gives it even another push as MCP is just another BFF and that's the sweet spot of GraphQL.
Side note, I'm not even defending GraphQL here, it's just about facts if we're looking at who's using and adopting GraphQL. If you look around, from Meta to Airbnb, Uber, Reddit or Booking.com, Atlassian or Monday, GitHub or Gitlab, all these services use GraphQL successfully and these days, banks are adopting it to modernize API access to their Mainframe, SOAP and proprietary RPC APIs.
How do I know you might say? I'm working with WunderGraph (https://wundergraph.com/), one of the most innovative vendors in the market and we're talking to enterprise every day. We've just came home from API days Paris and besides AI and LLMs, everyone in the enterprise is talking about API design, governance and collaboration, which is where GraphQL Federation is very strong and the ecosystem is very mature.
Posts like this are super harmful for the API ecosystem because they come from inexperience and lack of knowledge.
GraphQL can solve over fetching but that's not the reason why enterprises adopt it. GraphQL Federation solves a people problem, not a technical one. It helps orgs scale and govern APIs across a large number of teams and services.
Just recently there was a post here on HN about the problems with dependencies between Microservices, a problem that GraphQL Federation solves very elegantly with the @requires directive.
One thing I've learned over the years is that people who complain about GraphQL are typically not working in the enterprise, and those who use the query language successfully don't usually post on social media about it. It's a tool in the API tool belt besides others like Open API and Kafka. Just go to an API conference and ask what people use.
Side note, a lot of people these days build agents on top of APIs. GraphQL has selection sets, which allows you to select subsets of objects. This is quite handy when it comes to gents because of context window limitations.
I'm with WunderGraph, a vendor providing enterprise tooling for GraphQL.
First, I absolutely love Capn Proto and the ideas of chaining calls on objects. It's amazing to see what's possible with CapNweb.
However, one of the examples compares it to GraphQL, which I think falls a bit short of how enterprises use the Query language in real life.
First, like others mentioned, you'll have N+1 problems for nested lists. That is, if we call comments() on each post and author() on each comment, we absolutely don't want to have one individual call per nested object. In GraphQL, with the data loader pattern, this is just 3 calls.
Second, there's also an element of security. Advanced GraphQL gateways like WunderGraph's are capable of implementing fine grained rate limiting that prevent a client to ask for too much data. With this RPC object calling style, we don't have a notion of "Query Plans", so we cannot statically analyze a combination of API calls and estimate the cost before executing them.
Lastly, GraphQL these days is mostly used with Federation. That means a single client talks to a Gateway (e.g. WunderGraph's Cosmo Router) and the Router distributed the calls efficiently across many sub services (Subgraphs) with a query planner that finds the optimal way to load information from multiple services. While capNweb looks amazing, the reality is that a client would have to talk to many services.
Which brings me to my last point. Instead of Going the capNweb vs GraphQL route, I'd think more about how the two can work together. What if a client could use CapNweb to talk to a Federation Router that allows it to interact with entities, the object definitions in a GraphQL Federation system.
I think this is really worth exploring. Not going against other API styles but trying to combine the strengths.
Could I use this to iterate over my AI generated code until it's not detectable anymore? So essentially the moment you publish this tool it stops working?
I left a good paying job to start my first startup where I earned 1/3. The startup failed but I learned so much so that I tripled my initial salary in 2 years after the failing startup. Lesson learned? Take as much risk as you can.
We need to stop calling N+1 a GraphQL problem when it's simply an API problem (and REST has it at the HTTP layer while GraphQL has it as the resolver layer, which is actually an advantage for GraphQL, but people typically picture it differently). Anyways, this post tries a scientific/research-driven approach in the hopes to combat the AI slop that makes bad claims about GraphQL.
GraphQL is a really powerful query language, Fragments are extremely powerful, and the ecosystem is very healthy with multiple vendors and developments like oneOf directive, defer, etc.