Technology stack catalog

Linux, Apache, MySQL, and PHP — the classic open-source web hosting stack still underpinning large parts of the CMS and shared-hosting web.

Django web framework with PostgreSQL — a default production pairing recommended in Django’s own database docs.

FastAPI API services with PostgreSQL — a high-adoption Python API stack for microservices and ML-adjacent backends.

FastAPI with SQLAlchemy ORM against PostgreSQL — the standard Python async/sync API + ORM combination.

Flask microframework with PostgreSQL — a long-standing lightweight Python web/API stack.

Ruby on Rails with PostgreSQL — the default modern Rails database pairing for new apps.

Laravel PHP framework with MySQL — the most common Laravel starter database combination.

Laravel with PostgreSQL — common when teams prefer Postgres features while staying in the Laravel ecosystem.

NestJS TypeScript backend with PostgreSQL — a structured Node enterprise API stack.

NestJS services using Prisma against PostgreSQL for typed Node backends.

Express API with MongoDB — the backend half of MERN/MEAN without prescribing a frontend.

Express API with PostgreSQL — a minimal Node relational backend used widely outside full MERN/PERN branding.

Fastify high-performance Node framework with PostgreSQL — common for latency-sensitive APIs.

Hono web framework on Cloudflare Workers — an edge-native TypeScript API recipe.

Go services using the Gin HTTP framework with PostgreSQL — a common high-performance API stack.

Django with Celery workers, Redis broker, and PostgreSQL — the standard Django async-task production recipe.

NestJS APIs with PostgreSQL persistence and Redis for cache/queues — a common Node enterprise service shape.

Express services with PostgreSQL and Redis — classic Node session/cache + relational store pattern.

GraphQL APIs served by Apollo Server on Node.js — a primary GraphQL server recipe in the JS ecosystem.

Full-text search and analytics with Elasticsearch accessed from Node.js services.

Message queuing with RabbitMQ from Python workers and publishers.

Hono APIs running on the Bun runtime — an emerging high-performance JS server recipe.

Deno runtime with first-class TypeScript — an alternative JS server platform to Node.js.

JavaScript, APIs, and Markup — a decoupling pattern for pre-rendered sites served from CDNs with APIs for dynamic behavior.

Content-focused Astro sites deployed on Vercel — a common Jamstack-adjacent recipe for marketing and docs sites.

Client-side React SPA scaffolded with Vite and TypeScript — the default modern React tooling recipe outside Next.js.

React UI styled with Tailwind CSS — among the most common utility-CSS pairings in modern web apps.

Vue 3 SPA with Vite and TypeScript — the standard Vue tooling path.

Angular applications are TypeScript-first by design — the standard enterprise SPA frontend stack.

Desktop applications built with Electron and React — a common cross-platform desktop UI stack.

Tauri desktop shell with a React frontend — a lighter Rust-backed alternative to Electron.

React Native — Meta’s cross-platform mobile framework for iOS and Android using React.

React Native with Expo — the dominant managed workflow for shipping RN apps faster.

Flutter + Dart — Google’s cross-platform UI toolkit for mobile, web, and desktop.

Native iOS applications built with Swift and SwiftUI — Apple’s modern declarative UI stack.

Native Android UI with Kotlin and Jetpack Compose — Google’s modern Android UI toolkit.

PyTorch on Python — a leading research and production deep-learning stack.

TensorFlow on Python — Google’s established production ML framework stack.

Classical machine learning with scikit-learn on Python — the standard toolkit for non-deep-learning ML.

Serve PyTorch models behind FastAPI — a common inference API pattern for ML products.

NLP and multimodal models via Hugging Face Transformers on Python.

LLM application orchestration with LangChain on Python — a common agent/RAG application recipe.

Tabular data analysis and transformation with pandas on Python — foundational data-engineering tooling.

Large-scale distributed data processing with PySpark.

Apache Airflow for workflow orchestration with PostgreSQL as the metadata database — the standard Airflow production setup.

Analytics engineering with dbt models running on Snowflake — a leading modern data-stack pairing.

dbt transformations against PostgreSQL — common for smaller warehouses and local analytics stacks.

Event streaming with Apache Kafka consumed/produced from Python services.

ClickHouse as an OLAP analytics database — used for high-volume event and metrics analytics.

Containerized workloads with Docker images orchestrated by Kubernetes — the default cloud-native runtime pairing.

Infrastructure as code with Terraform provisioning Amazon Web Services resources.

Terraform provisioning Google Cloud Platform infrastructure.

Terraform provisioning Microsoft Azure infrastructure.

Spring Boot on the JVM with PostgreSQL — a dominant enterprise Java service stack.

ASP.NET / .NET applications with Microsoft SQL Server — the canonical Microsoft enterprise data stack.

.NET services with PostgreSQL — increasingly common for cloud-native .NET outside the Microsoft SQL Server default.

Local and small-deployment orchestration with Docker Compose running PostgreSQL — ubiquitous developer environment pattern.

Package and deploy Kubernetes applications with Helm charts.

Metrics collection with Prometheus and visualization with Grafana — the standard open-source observability pairing.

Configuration management and automation with Ansible on Linux hosts.

Nginx reverse proxy/load balancer packaged with Docker — common edge for containerized apps.

MongoDB, Express, React, and Node.js — a widely taught full-stack JavaScript pattern for SPAs with a document database.

MongoDB, Express, Angular, and Node.js — the Angular-centered counterpart to MERN for enterprise-leaning SPAs.

MongoDB, Express, Vue, and Node.js — the Vue.js variant of the classic Mongo + Express + Node pattern.

PostgreSQL, Express, React, and Node.js — a relational-database variant of MERN used heavily in production SaaS.

Next.js application backed by PostgreSQL — a common modern web recipe for SaaS products and marketing sites with a relational store.

Next.js with Prisma ORM against PostgreSQL — a dominant TypeScript full-stack recipe for typed database access.

Next.js with Drizzle ORM and PostgreSQL — a SQL-first TypeScript alternative to Prisma gaining adoption in the Next ecosystem.

Focused, full-stack Next.js recipe emphasizing end-to-end type safety with tRPC, Prisma ORM, and PostgreSQL.

Remix full-stack React framework with PostgreSQL — focused on web standards, nested routes, and server loaders.

Nuxt (Vue) full-stack framework with PostgreSQL for server routes and SSR applications.

SvelteKit application with PostgreSQL — a rising full-stack Svelte recipe for SSR and API endpoints.

Next.js frontend/backend with Supabase (Postgres + auth + APIs) — a popular managed backend recipe.

Next.js with Firebase Auth/Firestore/Hosting patterns — common for rapid product prototypes and realtime apps.