The typical startup stack

A lot of early startups in 2026 still look less like a grand architecture diagram and more like a backpack full of proven parts: React for screens, a database like PostgreSQL or MongoDB for data, Stripe for money, and deployment held together with scripts, cloud dashboards, and founder memory. (react.dev) (docs.stripe.com) (github.com) React keeps showing up because it lets teams build user interfaces from reusable components, which is a clean way for two engineers to keep shipping the same product without rewriting the page every week. The official React docs still describe it as a library for web and native user interfaces built from components, which is exactly the kind of boring reliability startups pay for. (react.dev 1) (react.dev 2) On the back end, the split is usually between a relational database and a document database. PostgreSQL stores rows and columns with strict relationships, while MongoDB stores flexible documents, so the choice often comes down to whether the team wants tighter structure or faster schema changes. (github.com) (mongodb.com) (postgresql.org) Stripe is the default payments layer because it turns “take a card and record the charge” into a documented workflow instead of a custom finance project. Stripe’s docs center the same promise startups want: quickstarts, hosted payment pages, subscriptions, invoicing, and APIs that let a small team start charging before they build a billing department. (docs.stripe.com 1) (docs.stripe.com 2) (docs.stripe.com 3) The messy part is deployment. A product can have a polished React front end and a clean database schema, then still depend on one person knowing which environment variable lives in which cloud console and which command fixes production after midnight. (github.com) (fastapi.tiangolo.com) That is why Docker keeps appearing in startup templates and job posts. Docker puts the app and its dependencies in a container, which is the software version of shipping the whole kitchen with the recipe so the code runs the same on a laptop, a staging server, and production. (docker.com) (github.com) (jobs.ashbyhq.com) The new ingredient is not a new stack so much as a new layer of helpers sitting on top of the old one. Cursor sells itself as “the best way to build software with AI,” Anthropic says Claude Code can understand a codebase, edit files, and run commands, Figma is adding AI features for design work, and Warp now calls itself an agentic development environment. (cursor.com) (claude.com) (figma.com) (warp.dev) That changes daily work more than it changes hiring checklists. The engineer still has to know where the React component ends, where the FastAPI or Django service begins, how the Structured Query Language database is modeled, and how the container gets deployed when the generated code breaks. (fastapi.tiangolo.com) (jobs.ashbyhq.com) (job-boards.greenhouse.io) Current job ads make that visible in plain text. Perplexity lists Python, Go, Rust, TypeScript, React, FastAPI, PostgreSQL, Redis, Docker, vLLM, and Amazon Web Services in one full-stack role, while other startup listings ask for React, TypeScript, Python, FastAPI or Django, relational databases, and continuous integration tools in the same breath. (jobs.ashbyhq.com 1) (jobs.ashbyhq.com 2) (job-boards.greenhouse.io) So the “typical startup stack” is still typical for a reason: it is not elegant, but it is legible. If you can move from a React component to a Python endpoint to a Structured Query Language query to a Docker deploy without getting lost, you are still unusually useful to a five-person company trying to look like fifty. (react.dev) (fastapi.tiangolo.com) (jobs.ashbyhq.com)