Node JS Development Services

We build backends that don't fall over at 2 AM. Our Node.js team has been shipping production APIs, real-time systems, and microservices for over a decade — for companies that can't afford downtime.

Talk to Our Backend Team
200+
Backend Projects Shipped
35+
Backend Engineers
99.9%
Avg. Uptime Across Projects
2014
Using Node.js Since

Companies We've Built Backends For

What Our Clients Say

What We Build with Node.js

Backend work isn't glamorous, but it's where things go wrong if you cut corners. Here's what we do.

REST & GraphQL APIs

Clean, well-documented APIs that your frontend team (or third-party integrators) will actually enjoy working with. We use NestJS or Fastify depending on complexity.

Microservices

We help teams break monoliths into services that can be deployed, scaled, and maintained independently. But we'll also tell you if you don't actually need microservices yet — premature decomposition causes more problems than it solves.

Real-Time Systems

Chat, live notifications, collaborative editing, price feeds — anything where data needs to arrive in milliseconds, not on the next page refresh. WebSockets, Socket.io, or SSE depending on the use case.

Serverless Functions

For workloads that are spiky or unpredictable, serverless makes a lot of sense financially. We build on AWS Lambda, Google Cloud Functions, and Vercel Edge — keeping cold starts low and costs predictable.

Enterprise Platforms

Multi-tenant systems with proper RBAC, audit trails, and the kind of boring-but-critical infrastructure that enterprises need. Not exciting, but it's what keeps production running.

Migration & Performance Tuning

Running a slow PHP or Java backend? We can migrate you to Node.js — or sometimes just fix the bottleneck in your existing stack. We're pragmatic, not dogmatic.

Where We Go Deep

Backend development has a lot of surface area. These are the areas where we've built real depth.

NestJS & Structured Backend Architecture

For anything beyond a small API, we reach for NestJS. Dependency injection, decorators, guards, pipes — it brings the structure that Node.js projects desperately need once you get past 20 endpoints. We pair it with Prisma or Drizzle for type-safe database queries.

NestJS Express Fastify Prisma Drizzle Swagger

Databases & Data Engineering

Postgres for most things. MongoDB when the data is genuinely document-shaped. Redis for caching, sessions, and queues. Elasticsearch when you need full-text search. We handle connection pooling, query optimization, and migrations — the unglamorous work that keeps your app from grinding to a halt.

PostgreSQL MongoDB Redis Elasticsearch Drizzle ORM Knex.js

DevOps & Deployment Pipelines

Every project gets Docker, a proper CI/CD pipeline, health checks, and structured logging from day one. Not as an afterthought, not "we'll add it later." We've seen too many projects go to production with manual SSH deploys. Never again.

Docker Kubernetes GitHub Actions Terraform PM2 Nginx

Why Teams Choose Us for Node.js

P95 Latency Under 100ms

OWASP Top 10 Covered

TypeScript Everywhere

CI/CD on Every Project

Same Team, Start to Finish

We Write the Tests Too

Honest Take on Node.js

Node.js isn't the right tool for every backend — and anyone who tells you otherwise is selling something. But for a very large class of problems, it's genuinely the best option available.

Where Node.js shines

Node.js was built for I/O. If your server spends most of its time waiting — waiting for database queries, waiting for API responses, waiting for file reads — Node.js handles that better than almost anything else. A single Node process can juggle thousands of these concurrent operations without breaking a sweat, because it never blocks on any single one.

This makes it a natural fit for APIs, real-time apps, and microservices. It's why Netflix moved to Node — they cut their startup time from 40 minutes to under a minute. It's why PayPal saw a 35% decrease in response time after switching from Java.

Where it doesn't

CPU-heavy work — video encoding, complex mathematical computations, heavy image processing — will choke a Node.js event loop. For those workloads, we use worker threads, offload to a queue, or recommend a Python development/Go service alongside Node. Being honest about this upfront saves our clients time and money.

We've learned the hard way that the best architecture is the one your team can actually maintain at 3 AM when something breaks. We optimise for debuggability and simplicity, not cleverness.

Our Node.js stack in practice

  • NestJS for structured APIs — because Express apps turn into spaghetti past a certain size
  • Prisma or Drizzle for database access — type-safe queries catch bugs before they reach production
  • Redis for caching and rate limiting — the performance difference is immediate and dramatic
  • Bull/BullMQ for background jobs — emails, reports, heavy processing off the request path
  • Pino for logging — structured JSON logs that your observability stack can actually parse

Every project gets the same foundation: TypeScript, automated tests, Docker, CI/CD, and health checks. It's not optional. We've been doing this long enough to know that skipping these "extras" always costs more later.

Trading Platform — 50K Price Updates Per Second

A fintech client needed their trading interface to show live prices from 12 exchanges simultaneously. We built the data pipeline in Node.js with WebSockets and Redis Pub/Sub. The hard part wasn't the throughput — it was graceful degradation. When an exchange feed drops, users see stale data with a clear indicator, not a crash. We built automatic reconnection, message deduplication, and circuit breakers for each feed.

Trading Platform — 50K Price Updates Per Second

SaaS Platform Serving 200+ B2B Clients

Each client needed their own data isolation, custom rate limits, and usage-based billing. We built it with NestJS, PostgreSQL with row-level security, and a custom API gateway that handles authentication, request routing, and metering. The system has been running for 18 months with zero data leaks between tenants — which, in multi-tenant land, is the only metric that matters.

SaaS Platform Serving 200+ B2B Clients

IoT Pipeline — 100K Sensors Reporting Every 10 Seconds

A manufacturing client had sensors on their factory floor generating a firehose of telemetry data. We built the ingestion layer in Node.js (it handles bursty I/O beautifully), pushed events through Kafka for processing, and stored time-series data in TimescaleDB. The dashboard shows real-time equipment health, and the alerting system has caught 3 potential failures before they caused downtime.

IoT Pipeline — 100K Sensors Reporting Every 10 Seconds

Common Questions

If your app is I/O-heavy (APIs, real-time features, integrations), Node.js is probably the right call. If you're doing heavy computation or data science, Python makes more sense. If you need raw CPU performance, Go is hard to beat. We don't push Node.js on projects where another tool is a better fit — we'll tell you honestly during our initial consultation.
TypeScript, full stop. We switched all our Node.js work to TypeScript in 2020 and haven't looked back. The upfront cost is minimal — maybe 10% more time writing code. The savings in debugging, refactoring, and onboarding are easily 3x that. Every new project starts with strict TypeScript config.
Express for small services or prototypes where simplicity matters most. Fastify when raw HTTP performance is a priority (it's measurably faster than Express). NestJS for anything with more than 15-20 endpoints — it forces a structure that keeps large projects maintainable. We've shipped production apps with all three.
We start by understanding your data model, not by picking a database. Relational data with complex joins? PostgreSQL. Document-oriented with flexible schemas? MongoDB. Need sub-millisecond reads? Redis. Full-text search? Elasticsearch. Most real-world projects use 2-3 of these together. We handle connection pooling, migrations, and query optimization so you don't hit scaling walls later.
Netflix serves 200+ million accounts on Node.js. LinkedIn handles 500+ million members. PayPal processes billions of dollars in transactions. So yes. The key is proper architecture — stateless services, horizontal scaling, caching, and load balancing. We've built Node.js systems serving 10M+ daily users with 99.99% uptime. It's not the language that fails at scale, it's the architecture.
Docker containers, GitHub Actions (or GitLab CI) for the pipeline, automated testing on every PR, staging environments that mirror production. We use PM2 or Kubernetes depending on the project's scale. Every deployment is automated — nobody SSHs into a server to pull code. Health checks, structured logging, and APM monitoring are included from the start, not bolted on later.

Need a Backend That Actually Scales?

Let's have a real conversation about your project. We'll tell you if Node.js is the right fit — and if it isn't, we'll point you in the right direction.

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