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Backend

Node.js Development Company

A single language across frontend and backend, with an event loop designed for high-concurrency I/O.

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How we work

Node.js runs JavaScript and TypeScript on the server with an event-driven, non-blocking I/O model. A single Node process can therefore hold thousands of concurrent connections open (websockets, long-polling requests, streaming responses) without starting a thread for each one. The model suits APIs, real-time features and backend-for-frontend layers well, and it lets a team share language, types and even validation logic between frontend and backend.

We build most Node.js backends on NestJS, which brings the structure (modules, dependency injection, decorators) that a plain Express app leaves you to invent yourself, or on Fastify when raw request throughput matters more than architectural scaffolding. Both outperform an unstructured Express setup for anything beyond a small service, and the choice between them usually comes down to whether the team wants Angular-style structure or a leaner, faster core.

Fit

When Node.js is the right choice, and when it is not

Good fit

  • The backend is primarily I/O-bound: calling databases, external APIs, and other services, rather than doing heavy in-process computation
  • You want to share types, validation schemas or business logic between a TypeScript frontend and the backend
  • The product needs real-time features (chat, live updates, notifications) built on websockets or server-sent events
  • You are building a backend-for-frontend layer that aggregates calls to several other services into one API tailored to a specific client
  • Your team is already strong in JavaScript or TypeScript and hiring backend-only specialists in another language would slow the project down

Consider something else

  • The workload is CPU-bound (image or video processing, heavy in-process computation, complex data transformation at scale): Node's single-threaded event loop makes this a poor fit without offloading to worker threads or a separate service in a language built for it
  • You need a batteries-included framework with a built-in admin panel and ORM conventions out of the box for a content-heavy application; Django or Laravel ship more of that by default
  • The team wants the strongest possible compile-time guarantees on a large financial or safety-critical system; a statically compiled language like Java, Go or C# gives stronger guarantees than TypeScript's erased, build-time-only types
  • You are inheriting a large existing JVM or .NET investment and the cost of introducing a second backend stack outweighs Node's benefits

What we build

What we build with Node.js

  • REST and GraphQL APIs

    NestJS-based APIs with typed request validation, structured modules and dependency injection for services, databases and external integrations.

  • Real-time features on websockets

    Chat, live dashboards, collaborative editing and notification systems built on Socket.IO or native WebSocket support, holding many concurrent connections per process.

  • Backend-for-frontend layers

    A tailored API in front of several internal or third-party services, aggregating and reshaping their responses for a specific web or mobile client.

  • High-throughput services on Fastify

    Lean, low-overhead services where request latency and throughput matter more than architectural scaffolding, such as a webhook receiver or an internal proxy.

  • Shared validation and types across the stack

    Zod schemas defined once and used for both API validation and generating the TypeScript types the frontend imports, closing the gap between the two.

  • Background jobs and queues

    BullMQ-based job queues for scheduled and retryable background work (emails, report generation, third-party sync) running alongside the main API process.

Ecosystem

Libraries and tools we pair it with

  • NestJS for structured, modular backend architecture
  • Fastify for lean, high-throughput services
  • Prisma or Drizzle for typed database access
  • BullMQ for background jobs and queues
  • Zod for request validation and shared types
  • Socket.IO for real-time features
  • Pino for structured, low-overhead logging
  • Vitest or Jest for unit and integration tests

NestJS versus Fastify versus plain Express

Express is still the most widely known Node framework, and it is also the least structured: routing, validation, error handling and dependency wiring are all left to whatever convention the original developer chose, which becomes a liability once more than one or two engineers touch the codebase.

NestJS solves that by imposing structure similar to Angular's: modules, decorators, dependency injection and a clear place for everything. It costs more boilerplate upfront and pays back on any service with real business logic and a team of more than one or two developers. Fastify sits in between: it is faster than Express and has a plugin architecture, but it does not impose NestJS's full architectural opinions, so we reach for it when raw throughput matters and the service is simple enough not to need NestJS's structure.

Handling CPU-bound work without abandoning Node

Node's event loop is single-threaded, so a CPU-heavy operation (resizing a large image, parsing a huge CSV, running a complex calculation) blocks every other request on that process while it runs. This is the most common performance mistake we see in Node codebases: a synchronous, expensive operation dropped directly into a request handler.

The fix is usually one of two paths. Worker threads move the CPU-bound work to a separate thread within the same Node process, appropriate for occasional, moderate-weight tasks. A dedicated background job queue (BullMQ, backed by Redis) moves the work out of the request-response cycle entirely, appropriate for anything that does not need to finish before the client gets a response. For workloads that are CPU-bound as their primary characteristic, such as a service that does nothing but transform large datasets, we typically recommend building that specific service in Go or another language better suited to raw computation, and keeping Node for the I/O-bound API layer around it.

  • Worker threads for occasional CPU-bound work inside an existing Node process
  • A background job queue for anything that does not need to block the response
  • A dedicated service in a compiled language for workloads that are CPU-bound by nature

FAQ

Questions about Node.js

Is Node.js fast enough for a high-traffic API?

For I/O-bound workloads, yes: the event loop model handles thousands of concurrent connections efficiently because requests spend most of their time waiting on a database or another service, not on CPU work. Where Node struggles is CPU-bound processing, which needs worker threads, a queue, or a separate service to avoid blocking the event loop.

Should we use NestJS or plain Express for a new API?

For anything beyond a small service maintained by one person, NestJS's structure (modules, dependency injection, consistent validation) pays back quickly once a second developer joins. Plain Express is reasonable for a very small, short-lived service where the overhead of NestJS's conventions is not worth it yet.

Can Node.js share code with a React or React Native frontend?

Yes, when both are written in TypeScript, which is our default. Validation schemas, API types and utility functions can live in a shared package and be imported by both the backend and the frontend, so a contract change breaks the build instead of breaking silently in production.

How does Node.js handle real-time features like chat or live notifications?

Through websockets, typically via Socket.IO, which manages connection state, reconnection and message broadcasting on top of the raw WebSocket protocol. A single Node process can hold a large number of open connections because it does not dedicate a thread per connection the way some other server models do.

When would you recommend against Node.js for a backend?

When the core workload is CPU-bound rather than I/O-bound, such as heavy data transformation, video processing or numerically intensive computation. Node can still front that kind of service, but the heavy lifting belongs in a worker process or a separate service built in a language designed for raw computation.

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