Encore vs Serverless Framework

Architecture Differences

Serverless Framework is function-based. Each endpoint is a separate Lambda function that scales to zero when not in use. This is cost-efficient for sporadic traffic but introduces cold starts and makes it harder to share state between functions.

Encore runs persistent services that stay warm. No cold starts, and you can structure your code as traditional services with shared state and connections. This is better for consistent traffic and complex business logic.

Both deploy to your AWS account. Encore manages the infrastructure automatically; Serverless requires manual configuration of each AWS service.

Configuration Approach

Serverless Framework uses YAML configuration files. You define functions, events, and resources in serverless.yml. Complex applications can have hundreds of lines of YAML that's separate from your application code.

Encore uses infrastructure-from-code. Declare a database as a TypeScript object, and Encore creates RDS or Cloud SQL when you deploy. No YAML, no CloudFormation templates.

import { SQLDatabase } from "encore.dev/storage/sqldb";
import { api } from "encore.dev/api";

const db = new SQLDatabase("users", {
  migrations: "./migrations",
});

export const getUser = api(
  { method: "GET", path: "/users/:id" },
  async ({ id }: { id: string }) => {
    return db.queryRow`SELECT * FROM users WHERE id = ${id}`;
  }
);

// No YAML needed - Encore provisions everything

AI-Assisted Development

With Serverless Framework, infrastructure lives in YAML files separate from your code. AI agents like Cursor and Claude Code can generate functions, but they often produce incorrect YAML configurations that are hard to review and debug.

Encore defines infrastructure as TypeScript objects alongside your application code. AI agents see everything in one context: your APIs, databases, queues, and how they connect. This makes AI-generated code accurate, reviewable, and safe to deploy.

Built-in guardrails, auto-documentation, and observability ensure your systems stay maintainable, even when AI writes most of the code.