Backend
Node.js
We build event-driven Node.js backends for the systems where throughput, real-time behaviour and uptime are the whole point — not a nice-to-have.
Overview
Node.js runs JavaScript on the server, which makes it a natural fit for fast, event-driven backends — APIs, real-time features, and services that share language and even code with a JavaScript front end. That shared-language advantage is real: one team, one set of tooling, less translation between the two halves of a system.
We build APIs and services on Node where its concurrency model fits the workload, and we are honest about where it does not — CPU-bound work is better served elsewhere. The judgement about which is which is part of what you are hiring.
Best for — Fast, concurrent backends and APIs, especially alongside a JavaScript front end.
Why teams choose Node.js
One language, both ends
Share code and skills between front end and backend — one team, less translation.
Great at concurrency
Handles many simultaneous connections efficiently — ideal for real-time and APIs.
Fast to ship
A vast package ecosystem and quick iteration speed development.
Why businesses choose Node.js
- It handles thousands of simultaneous connections on modest hardware, which is exactly what real-time and streaming workloads need.
- One language across the stack means a single team can own the API and the front end, with less translation and fewer handoff bugs.
- The npm ecosystem is the largest of any runtime, so common infrastructure is a dependency away rather than a build.
- It starts fast and stays lean, which makes it a natural fit for microservices and serverless functions that scale to zero.
What we build with Node.js
The capabilities this technology is genuinely strong at — and what we most often build with it.
Event-driven APIs
Non-blocking REST and GraphQL APIs that stay responsive while thousands of requests are in flight at once.
Real-time & WebSockets
Live dashboards, chat, presence, notifications and collaborative features over persistent socket connections.
Streaming
Streaming uploads, downloads and data processing that handle large payloads without loading them fully into memory.
Microservices
Small, independently deployable services with fast startup — well matched to a service-oriented architecture.
BFF & API gateways
Backend-for-frontend layers that shape data for your UI and sit cleanly in front of downstream services.
Event pipelines
Queue- and stream-backed workers for asynchronous jobs, integrations and background processing.
Use cases
Real-time platforms
Trading screens, live tracking, chat and collaboration tools where updates must arrive in milliseconds.
High-throughput APIs
Public and internal APIs serving heavy concurrent traffic with predictable latency.
Streaming media & data
Systems that move large files or continuous data streams without buffering everything in memory.
IoT & telemetry
Ingesting and routing high volumes of small messages from many connected devices.
When Node.js is the right choice
- Right for I/O-heavy APIs, real-time features and streaming
- Right when sharing language and code with a JavaScript front end pays off
- Efficient for high-concurrency services with modest per-request compute
- Not the pick for heavy CPU-bound processing — we use the right tool there
Node.js: pros and cons
Strengths
- Excellent for I/O-heavy, high-concurrency APIs and real-time features
- Shared language with the front end reduces team and tooling overhead
- The largest package ecosystem of any runtime (npm)
- Fast startup and iteration, well-suited to microservices
Trade-offs
- Single-threaded model is a poor fit for CPU-bound heavy computation
- Callback and async patterns can bite teams new to the model
- Dependency sprawl needs active management for security and size
- Long-running heavy tasks belong in a different tool
Event-driven architecture
Node.js runs on a single-threaded event loop with non-blocking I/O. Instead of dedicating a thread to each connection and letting it sit idle while it waits on a database or network call, Node registers a callback and moves on — so a single process can hold thousands of open connections while using very little memory. That model is why Node is so well suited to real-time and I/O-heavy workloads, and why it behaves so differently from thread-per-request platforms.
We design around that grain rather than against it: CPU-bound work is moved off the event loop into worker threads or separate services so it never blocks request handling, backpressure is respected on streams so a fast producer cannot overwhelm a slow consumer, and the process is treated as disposable so it can be scaled horizontally behind a load balancer. Get those three things right and Node scales cleanly; get them wrong and it stalls under exactly the load it was chosen for.
Performance & concurrency
Node’s performance story is about concurrency, not raw single-operation speed. Because I/O does not block, a well-built Node service serves far more simultaneous requests per core than a thread-per-request stack — but only if nothing on the hot path blocks the event loop. We profile for exactly that: synchronous work, unbounded loops and heavy JSON serialization are the usual culprits, and they are found with measurement, not guesswork.
At scale we run multiple Node processes — one per core via clustering or, more often, multiple container replicas behind a load balancer — so the platform uses the whole machine and a single crashed process never takes the service down. Caching with Redis, connection pooling, and streaming large responses keep latency flat as traffic grows.
Security
Most Node security risk lives in the dependency tree, not in code you wrote — so we treat the supply chain as a first-class concern: locked dependencies, automated vulnerability scanning in the pipeline, and a bias toward fewer, well-maintained packages over many casual ones. Secrets stay out of the codebase and in a managed store, and every input crossing a trust boundary is validated and typed.
Beyond that it is the fundamentals done consistently — authentication and authorization enforced at the right layer, rate limiting and sensible timeouts against abuse, and least-privilege access between services — wired into delivery so each release ships defensible rather than being hardened after a scare.
Scalability
Node scales horizontally by design. Because a process is lightweight and stateless when built correctly, you scale by running more replicas behind a load balancer rather than by buying a bigger box — which is the cheaper and more resilient direction. We keep session and shared state out of the process (in Redis or the database) precisely so any replica can serve any request and the fleet can grow and shrink with demand.
For systems that outgrow a single service, we split along real boundaries into microservices that communicate over queues or events, so load on one part does not drag down the rest. The result is a backend that meets a traffic spike by adding capacity in seconds rather than falling over.
Node.js integrations & ecosystem
The technologies we most often pair with it — each links to how we work with it.
How we build Node.js systems
We start by deciding the boundaries — what is one service versus many, where state lives, and how the pieces talk — because those are the decisions that are costly to change once traffic arrives. TypeScript is on from day one; on a backend that other services depend on, the type system pays for itself many times over in bugs that never ship.
From there it is short cycles against working software, with load and integration tests that exercise the concurrency the system was chosen for, and observability — structured logs, metrics and traces — shipped with each feature so production behaviour is visible rather than inferred.
The service behind it
Delivered throughCustom Software DevelopmentWhat we build with Node.js
The disciplines this technology most often shows up in — from a first build to taking over and stabilising an existing one.
How we deliver
- 01
Discover
We map the system, the constraints and the business it serves — including the parts nobody documented.
Architecture brief
- 02
Architect
Decisions get made, written down and defended before a line of production code exists.
Decision records
- 03
Build
Short cycles against working software. You see progress in the product, not in a status deck.
Shipping increments
- 04
Operate
Monitoring, incident response and iteration. The system is alive, so the engagement is too.
Runbooks & SLOs
Industries we use Node.js in
Domain knowledge changes what gets built. A few of the sectors we know before the first meeting.
Also in Backend
Why teams choose us for Node.js
We operate what we build
We stay on the pager after launch, so we design Node services for the 3am incident, not just the demo.
Concurrency is the point
We build for the load the system was chosen for and prove it with load tests, rather than hoping it holds.
Senior, end to end
The engineers who architect your backend are the ones who write it — no junior hand-off after the sale.
Typical timeline
- 01
Discovery
1–2 weeks to map the workload, boundaries and non-functional requirements.
- 02
Architecture
1–2 weeks to decide and document the service design, data model and scaling approach.
- 03
Build
Short cycles against working software; a first production-ready API in weeks, not months.
- 04
Operate
Load testing, observability and iteration as real traffic arrives.
How pricing works
- We do not publish a day rate for Node.js work, because the cost is driven by the system, not the language. A well-scoped API is a very different engagement from a real-time platform with strict latency targets.
- The drivers we price against are concurrency and latency requirements, the number of integrations, whether we are building fresh or stabilising an inherited system, and the operational bar (uptime, compliance, on-call). Most engagements begin with a paid discovery phase so the estimate reflects your real requirements.
Hire Node.js engineers
Need Node.js capacity on your own team? We embed named senior engineers into your existing team — reporting to your leads, working in your rituals — so you add capacity without a hiring cycle.
Hire Node.js engineersCommon questions
Is Node.js fast enough for a high-traffic backend?
For I/O-heavy, high-concurrency workloads — APIs, real-time features, streaming — Node is one of the best-suited runtimes there is, because non-blocking I/O lets a single process serve far more simultaneous connections than a thread-per-request stack. The caveat is CPU-bound work, which we deliberately move off the event loop into workers or separate services so it never blocks request handling.
Can you build real-time features like chat or live updates?
Yes — real-time is one of Node’s strongest use cases. We build live dashboards, chat, presence, notifications and collaborative editing over WebSockets, with the connection management, scaling and fallback behaviour that keep them reliable once thousands of users are connected at once.
Can you take over an existing Node.js codebase?
Yes, and a lot of our Node work is exactly that. We start by reading the code and its history — dependencies, boundaries, where the event loop is being blocked — before changing anything, then stabilise and modernise from a position of understanding rather than proposing an immediate rewrite.
Do you use TypeScript with Node.js?
By default. On a backend that other systems depend on, static types catch whole classes of bugs before they ship and make the code far safer to change later. We would only skip it for a genuine reason, and we would tell you what that reason is.
How do you scale a Node.js application?
Horizontally. We keep processes stateless — session and shared state live in Redis or the database — so any replica can serve any request, and we run many replicas behind a load balancer that grows and shrinks with demand. For larger systems we split along real boundaries into microservices so load on one part does not affect the rest.
Building on Node.js?
A technical conversation with the engineers who would do the work. If we are not the right fit, we will say so on the call.