Make vs Windmill: Automation Engines Compared

First published 2026-06-26 · Updated June 26, 2026 · Comparison · 15 min read

TL;DR / Quick Take

When building automated backend workflows, teams must choose between visual no-code builders and code-first execution engines. Make (formerly Integromat) and Windmill are the two leading options in 2026. This guide compares Make's visual drag-and-drop integration editor with Windmill's self-hosted, developer-centric code-execution pipeline.

Make
Visual drag-and-drop editor
Windmill
Self-hosted code runner
Performance
Low latency, high throughput

Visual Scenario Building vs. Code-First Workflows

Make and Windmill cater to different organizational needs and skill levels. Product and growth teams must evaluate where their automations reside in the software stack to select the appropriate platform.

  • Make: Features a beautiful visual interface. It is excellent for growth marketers, product managers, and operations teams building workflows with pre-built app integrations (Slack, Google Sheets, Salesforce, etc.) without writing any code. It allows rapid prototyping but can become difficult to manage for complex logic structures.
  • Windmill: Built for software engineers. It turns scripts written in Python, TypeScript, Go, or Bash into secure, structured API endpoints and background workers. Workflows are defined using code, with support for version control (git), local testing, and CI/CD pipelines. This developer-centric approach makes it easy to integrate with existing software practices.

Visual editors are great for simple triggers and notifications. However, when your workflow requires complex logic—such as nested loops, deep API error-handling, database rollbacks, or custom cryptography libraries—representing this visually in Make results in an unmaintainable "spaghetti" of bubbles and routers. In Windmill, the same logic is represented as a single, clean TypeScript file, making it easy to review and debug.

Performance, Latency, and Self-Hosting

A major bottleneck for enterprise-grade integrations is processing latency. Because Make runs entirely in a shared cloud environment, each step in a scenario requires communicating with Make's servers. A typical scenario with 5 modules can take between 500ms and 3 seconds to complete, making it unsuitable for real-time checkout flows or high-speed webhook routes. Windmill is typically self-hosted inside your private VPC. Workflows are compiled into lightweight steps and executed in sandboxed environments (using Deno or Python interpreters), achieving sub-10ms latency. This allows engineers to use Windmill for real-time data syncs and low-latency API triggers.

Writing Workflows in Windmill: TypeScript Task Example

In Windmill, you write reusable components as standard script functions. These functions are typed, meaning the Windmill frontend automatically generates validation forms and checks parameters during runtime.

Below is a structured TypeScript code block showing a Windmill database lookup and webhook trigger script:

import { Client } from "https://deno.land/x/postgres@v0.17.0/mod.ts";

export async function main(params: {
  userId: string;
  npsScore: number;
  npsComment: string;
}) {
  const client = new Client(Deno.env.get("PG_CONN_STRING"));
  await client.connect();
  
  // 1. Insert NPS feedback into local database
  await client.queryArray(
    "INSERT INTO user_feedback (user_id, score, comment) VALUES ($1, $2, $3)",
    [params.userId, params.npsScore, params.npsComment]
  );
  await client.end();

  // 2. Trigger conditional webhook for low scores
  if (params.npsScore <= 6) {
    const res = await fetch(Deno.env.get("SLACK_WEBHOOK_URL")!, {
      method: "POST",
      headers: { "Content-Type": "application/json" },
      body: JSON.stringify({
        text: `⚠️ Alert: Low NPS score of ${params.npsScore} received from User ${params.userId}`
      })
    });
    return { status: "ALERTED_SLACK", slackResponse: res.status };
  }

  return { status: "FEEDBACK_LOGGED" };
}

Detailed Comparison: Make vs. Windmill

Metric Make (formerly Integromat) Windmill.dev
Deployment Model Cloud-hosted SaaS (Make's infrastructure) Self-hosted (Docker/Kubernetes in your own VPC)
Developer DX No-code drag-and-drop bubbles TypeScript, Python, Go, Bash scripts + UI builder
Version Control No native Git support (manual JSON exports) Full Git integration (declarative YAML + code)
Pricing Model Per operation run (costs scale with volume) Open source (Self-hosted AGPL-3.0 is free)
Data Residency US/EU cloud database (compliance hazard) 100% on-premise local servers (ideal for DPDP)

Security & Indian DPDP Act Compliance

For fintechs and healthtechs in India, compliance with the DPDP Act 2023 is mandatory. Make routes transaction payloads through their cloud networks, which means customer PII (emails, phone numbers, transaction values) leaves your local servers. This can result in serious compliance infractions.

Because Windmill can be hosted entirely on your local AWS/GCP servers in Mumbai, no data ever leaves your secure cloud environment. You maintain full ownership of all secrets, database credentials, and execution logs, satisfying both compliance audits and internal cybersecurity standards.

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