What are the different ways to connect my app's frontend and backend?

Every app you have ever used is two things talking to each other. There is the part you see (the screens, buttons, and forms) and there is the part you never see: the logic that stores your data, runs calculations, and decides what to show you. How those two halves communicate is one of the most consequential technical decisions in any project, and most founders never get to weigh in on it.

That is not a gap in your technical knowledge. It is a gap in how agencies explain their choices. This article closes that gap.

Picture a restaurant. You sit at a table (the frontend). The kitchen prepares your food (the backend). The waiter moves between them. In an app, the connection between frontend and backend is the waiter. It carries your request to the kitchen and brings the result back to your table.

When you tap "sign in" on an app, your phone does not already have your account information sitting on it. It sends a request to a server somewhere, the server checks your credentials, and it sends back a response: "yes, let them in" or "wrong password." That round trip happens in under a second. The mechanism that makes it work is called an API, a defined channel between the two halves of your app.

Every app has this. The question is which type of channel to use, because each one has different costs, different strengths, and different situations where it starts to cause problems.

There are three approaches in common use, and they suit different kinds of apps.

REST (Representational State Transfer) is the default choice for roughly 80% of apps built today (RapidAPI, 2022 State of APIs). The idea is straightforward: your frontend asks for a specific thing, the backend sends that specific thing back. Each request is self-contained. The frontend says "give me this user's profile" and the backend says "here it is."

REST is fast to build, easy to document, and well understood by almost every developer on the planet. When your team turns over, and at some point it will, any replacement developer can read your API and understand it in an afternoon. Maintainability compounds over years.

GraphQL takes a different approach. Rather than the backend deciding what data gets sent, the frontend describes exactly what it needs and the backend assembles it. A screen that needs a user's name, their last three orders, and the delivery address for each order can ask for all of that in a single round trip instead of making three separate requests.

This becomes meaningful when your product has many screens with very different data needs: a dashboard that pulls from eight different data sources, a mobile app where every byte of data costs the user battery life. GitHub switched their public API to GraphQL in 2016 specifically because their developer community was making too many requests to assemble the data they needed. Shopify's storefront API is GraphQL for the same reason: merchants need wildly different combinations of product data depending on what they are building.

But GraphQL adds complexity. It requires more setup time, more careful thinking about security (it is easier to accidentally expose data you did not intend to), and developers who are comfortable with it. For an MVP, that tradeoff almost never makes sense.

A real-time connection is the third approach. REST and GraphQL both work on a request-response model: you ask, the server answers, the line goes quiet. A real-time connection stays open. The server can push updates to your app the moment something changes, without waiting for the app to ask.

This is what powers chat applications, live delivery tracking, collaborative tools where two users edit the same document, and stock price displays. Without a persistent connection, building these features means the app has to check the server every few seconds to see if anything changed, which is expensive, slow, and drains mobile batteries quickly. A proper real-time connection eliminates that polling cycle.

The cost is infrastructure that never sleeps. A standard server handles requests and moves on. A real-time server maintains an open channel with every connected user simultaneously, which means more memory, more compute, and more engineering to handle failures gracefully. A 2022 survey by Ably found that real-time features add 20–40% to backend development costs on average.

Start with the simplest question: does anything in your app need to update the moment it changes, without the user refreshing or tapping something?

If the answer is no, REST is almost certainly the right choice. A booking platform, a SaaS dashboard, an e-commerce store, a content app, a marketplace: these products request data when a user navigates to a screen and display what comes back. REST handles this cleanly, ships faster, and costs less to maintain.

If specific features require live updates (a chat thread, a notification that fires the instant an order changes status, a map that shows a driver's position moving in real time), the question becomes whether those features are core to your product or secondary. If they are secondary, you can launch with REST and layer in real-time connections for just those features later. Many apps do exactly this: the main product runs on REST, and the live chat or live tracking module runs on a separate real-time service.

GraphQL earns its place when you have a mature product with many surfaces consuming the same data differently. A mobile app, a web app, and a third-party developer platform all making requests to the same backend is a reasonable case for GraphQL. An MVP with two screens is not.

A useful frame: think about who will maintain this product in two years. REST documentation is so standard that a developer who has never seen your codebase can integrate with your API in a day. GraphQL requires familiarity with the schema and query language. Real-time infrastructure requires understanding of connection handling, reconnection logic, and failure modes. Each step up in capability is also a step up in the expertise required to keep it running. The 2022 Stack Overflow Developer Survey found that only 29% of developers had worked with GraphQL in the past year, compared to over 70% with REST. The talent pool matters when you are hiring or bringing on contractors.

Cost differences between connection approaches are real but often misunderstood. The gap is not in the frontend work; screens look the same regardless of which approach the backend uses. The gap shows up in backend complexity, testing requirements, and time to a working first version.

Western agencies building on real-time infrastructure often quote $40,000–$60,000 for the backend alone on a product where live features are central. A global engineering team with the same capabilities delivers comparable infrastructure for $15,000–$22,000, because the engineering hours cost less and modern tooling has reduced the boilerplate that used to pad these invoices.

For most apps landing in the MVP range, REST adds no premium at all. It is the default approach and the baseline cost. The decision to use GraphQL or real-time connections should be driven by whether your product genuinely needs them, not by a preference for newer technology.

One number worth anchoring to: a survey by Postman in 2022 found that 89% of developers reported their organizations use REST APIs. GraphQL adoption has grown but remains a secondary choice in most stacks. Default to what the majority of the industry defaults to, and you reduce your risk on every dimension: hiring, handoffs, debugging, and future development.

Timespade builds across all three approaches, and the decision process on every project starts the same way: what does your product actually need in the first six months? If real-time features appear in month three of your roadmap, build REST first and add the real-time layer when you have real users telling you it is worth it.

If you want a clear answer on which approach fits your specific product, book a discovery call. You will have wireframes and a technical recommendation within 24 hours.