Node.js
A JavaScript/TypeScript runtime we use to build backend services, APIs, and integration layers — chosen for its fit with I/O-heavy and API-driven workloads, not applied as a one-size-fits-all backend default.
- Web client
- Mobile client
- REST / GraphQL endpoint
- Auth middleware
- Domain service
- Business logic
- Background job queue
- Worker process
- Primary datastore
- Third-party API
- Webhook receiver
- Structured logging
- Metrics & tracing
Node.js is a JavaScript runtime we use to build backend services and APIs — from customer-facing platforms to internal operational systems and integration layers. It's a strong default for I/O-heavy, API-driven backends and for teams that benefit from sharing TypeScript across frontend, mobile, and backend, though it isn't the right choice for every workload.
Where it fits
Node.js runs JavaScript and TypeScript on the server, which lets a team share code, types, and validation logic between backend, web frontend, and a React Native mobile app. For businesses building more than one client on top of the same backend, that shared type layer reduces duplicated logic and a class of bugs caused by frontend and backend silently disagreeing about a data shape.
Its non-blocking I/O model makes it well suited to workloads dominated by waiting on external systems — API calls, databases, third-party services — rather than heavy in-process computation. Many business backends, especially integration layers and API gateways, spend most of their time waiting on I/O, which is exactly the pattern Node.js is built around.
It is not the only reasonable choice, and we don't treat it as one. For CPU-intensive workloads — heavy data processing, complex numerical computation — other runtimes are frequently a better architectural fit, and we say so rather than forcing Node.js to cover every workload in a system.
Core capabilities
- REST and GraphQL API development
- Backend-for-frontend layers serving web and mobile clients
- Webhook and event-driven integration endpoints
- WebSocket-based real-time features
- High-concurrency API gateways and proxies
- Integration layers connecting multiple external systems
- Shared types and validation schemas across backend and frontend
- A single language across web, mobile (React Native), and backend teams
- Faster onboarding when a team already knows JavaScript/TypeScript
Common use cases
- Customer-facing platform backendsThe API and business-logic layer behind a web or mobile product.
- Internal operational systemsBackend services for internal tools — dashboards, workflow systems, admin platforms.
- Integration and data layersServices that consolidate and normalise data from multiple existing systems (ERP, MES, WMS, third-party APIs).
- Real-time featuresLive status updates, notifications, or collaborative features built on WebSocket connections.
Architecture & integration considerations
- CPU-bound work isolationHeavy computation is offloaded to worker processes, queues, or a different runtime entirely, rather than blocking the main event loop.
- Type safety at the boundariesRuntime schema validation (not just compile-time TypeScript types) at API boundaries, since TypeScript's guarantees don't extend to untrusted input.
- Service decompositionA decision, made per project, on whether a single service or multiple smaller services fits the team's operational maturity — not an automatic microservices default.
- Dependency managementDeliberate vetting of third-party packages, given the size and variability of the Node.js package ecosystem.
Strengths
- Strong fit for I/O-heavy workloadsNon-blocking I/O handles high volumes of concurrent API/database/network operations efficiently.
- Shared language across the stackOne language (TypeScript) across backend, web frontend, and React Native mobile reduces context-switching and duplicated logic.
- Fast iterationA large ecosystem and fast startup/build cycle support quick iteration during active development.
- Mature for production useA known quantity in production — the failure modes, scaling limits, and operational tooling are well understood, so less time goes into discovering surprises and more into building the actual system.
Trade-offs & limitations
- Not ideal for CPU-heavy workloadsSingle-threaded-by-default execution means heavy computation can block other requests unless explicitly offloaded — other runtimes are often a better fit for that work.
- TypeScript is not a runtime guaranteeType checking happens at compile time; without runtime validation at system boundaries, malformed data can still reach application logic.
- Package ecosystem variabilityThe npm ecosystem's size cuts both ways — high-quality libraries exist alongside poorly maintained ones, requiring deliberate vetting.
- Not inherently faster than every alternativeIts efficiency advantage is workload-dependent; for some backend workloads, other runtimes or languages perform as well or better.
When to use it
- The backend is primarily API-driven and I/O-heavy rather than computation-heavy
- The team benefits from sharing TypeScript types across backend, web, and mobile
- Real-time or high-concurrency features are part of the requirements
- Fast iteration speed during early product development is a priority
When another option may be more appropriate
- The workload is dominated by CPU-intensive processing (heavy data transformation, numerical computation)
- An existing backend in another language is stable and a rewrite isn't justified
- Strict compile-time and runtime type guarantees across the entire system outweigh the benefits of a shared JavaScript/TypeScript stack
- Specific libraries or platform requirements are only mature in another ecosystem
Relevant services
- Custom Software DevelopmentDesign and development of secure, scalable custom software for companies across Sweden and the Nordic region.
- AI DevelopmentProduction-oriented AI systems, assistants, RAG platforms and intelligent automation for Nordic businesses.
- Mobile App DevelopmentProduct-focused mobile application development for iOS and Android, from architecture and UX to release and ongoing evolution.
Relevant industries
- ManufacturingCustom manufacturing software, operational platforms and connected systems for companies modernising production across Sweden and the Nordic region.
- Logistics and MobilityCustom logistics, fleet, mobility and transport software for companies managing complex operations across the Nordic region.
- Climate Tech and EnergySoftware platforms, data systems and digital products for energy, electrification and climate-focused businesses across the Nordic region.
Representative solutions
Alternatives & complementary technologies
- PythonOften a better fit for data-processing- or AI/ML-adjacent backend workloads, or where an existing Python ecosystem already exists.
- GoA common choice for CPU-bound services or where a statically typed, compiled runtime is preferred for performance-critical paths.
- Java/Kotlin (JVM)A reasonable fit for large, long-lived enterprise systems already standardised on the JVM ecosystem.
Frequently asked questions
Is Node.js always faster than other backend runtimes?
No. It's efficient for I/O-heavy, concurrent workloads, but other runtimes can outperform it on CPU-intensive work. The right choice depends on the workload, not a blanket performance claim.
Can Node.js scale to handle significant traffic?
Yes, with appropriate architecture — but scalability depends on how the system is designed (caching, queuing, horizontal scaling), not on the runtime alone providing it automatically.
Do you use Node.js for every backend project?
No. We use it where it fits — API-driven, I/O-heavy backends, and projects that benefit from shared TypeScript with a web or React Native client — and recommend other runtimes when the workload calls for them.
Does using Node.js mean the frontend and backend share all code?
Not all code, but the language and, where useful, type definitions and validation schemas — reducing duplication without merging frontend and backend into a single undifferentiated codebase.
Further reading
- API Design Practices for Long-Lived, Multi-Consumer SystemsA technical reference on API design for systems integrated against for years: resource modeling, versioning, auth, pagination, errors, and compatibility.
- Event-Driven Architecture: When and How to Use ItA technical guide to event-driven architecture: patterns, message broker fundamentals, real tradeoffs, and when to choose events over a synchronous API call.
- Microservices vs. Monolith: Choosing the Right ArchitectureA technical comparison of microservices and monolithic architecture: tradeoffs, Conway's Law, data consistency, and a practical decision framework.
Considering Node.js for your next project?
Tell us what you're building — we'll confirm whether this is the right technology choice before recommending anything.