Temporal vs Make for API-First Workflows

What You'll Need

• n8n Cloud or self-hosted n8n instance
• Hetzner VPS or Contabo VPS for hosting Temporal locally
• DigitalOcean as an alternative for cloud deployment
• Namecheap if you need a domain
• API keys for your target services (Stripe, GitHub, Slack, etc.)
• Docker and Docker Compose (free, open-source)
• Node.js 18+ and npm

Table of Contents

• What's the Real Difference Between Temporal and Make?
• Temporal: The Orchestration Engine Approach
• Make: The Visual No-Code Platform
• Building Your First Temporal Workflow
• Building the Same Workflow in Make
• Cost and Infrastructure Breakdown
• Getting Started

What's the Real Difference Between Temporal and Make?

I've spent the last three years building API-first workflows for SaaS companies, and this question comes up constantly. The short answer? Temporal and Make.com solve the same business problem—automating API calls across services—but they approach it like night and day.

Temporal is a workflow orchestration platform. It's open-source, runs on your infrastructure, and treats workflows like distributed systems. You write code. You version control it. You deploy it like a regular application.

Make is a visual, cloud-hosted workflow builder. You drag and drop modules, connect APIs with a GUI, and hit publish. No code required.

The choice between them depends on your tolerance for infrastructure complexity, your budget constraints, and whether you want the flexibility of code or the simplicity of no-code. I've helped teams switch from expensive SaaS solutions like Zapier to self-hosted alternatives to reduce their SaaS bill, and this comparison is foundational to that conversation.

If you're building workflows that require complex branching logic, error handling, retry strategies, or need to integrate deeply with your existing codebase, Temporal wins. If you want to ship something in hours without touching a terminal, Make is faster. Let me show you how both work in practice.

Temporal: The Orchestration Engine Approach

Temporal was created by engineers from Uber and Doordash who needed a system that could handle reliability at scale. It's not a SaaS platform—it's a framework. You run the Temporal server yourself, write workflows in TypeScript or Python, and execute them against that server.

Here's why developers love it:

Automatic retries and error handling – If an API call fails, Temporal retries it with exponential backoff without you writing retry logic.

Durable execution – If your worker crashes mid-workflow, Temporal replays it from the last checkpoint. No data loss.

Visibility – You get a full history of every workflow execution with timestamps, inputs, outputs, and failures.

Cost efficiency – No per-execution fees. You pay only for the infrastructure running your server.

This is especially important if you're handling high-volume workflows. Imagine running 10,000 API calls per day through Zapier. You'd hit their usage limits fast. With Temporal, those 10,000 calls cost you only the server resources needed to run them.

Setting Up Temporal Locally

Let's get a Temporal server running on your Hetzner VPS or local Docker setup.

mkdir temporal-workflow && cd temporal-workflow
curl -O https://raw.githubusercontent.com/temporalio/docker-compose/main/docker-compose.yml
docker-compose up -d

Once the server is running on localhost:7233, create a package.json:

{
  "name": "temporal-api-workflow",
  "version": "1.0.0",
  "main": "index.js",
  "scripts": {
    "worker": "ts-node src/worker.ts",
    "workflow": "ts-node src/run-workflow.ts"
  },
  "dependencies": {
    "@temporalio/client": "^1.11.0",
    "@temporalio/worker": "^1.11.0",
    "@temporalio/workflow": "^1.11.0",
    "axios": "^1.6.0",
    "ts-node": "^10.9.0",
    "typescript": "^5.0.0"
  }
}

Install dependencies:

npm install

Now create your workflow definition in src/workflows.ts:

import { proxyActivities } from '@temporalio/workflow';
import type * as activities from './activities';

const { fetchUserFromStripe, sendSlackNotification, logToDatabase } = proxyActivities<typeof activities>({
  startToCloseTimeout: '10 seconds',
  retry: {
    initialInterval: '1 second',
    maximumInterval: '1 minute',
    maximumAttempts: 5,
  },
});

export async function processStripeWebhook(customerId: string) {
  const user = await fetchUserFromStripe(customerId);

  if (user.status === 'active') {
    await sendSlackNotification({
      channel: '#billing',
      message: `User ${user.email} is active and has ${user.subscriptions.length} subscriptions`,
    });
  }

  const logResult = await logToDatabase({
    customerId,
    status: user.status,
    timestamp: new Date().toISOString(),
  });

  return {
    processedAt: new Date(),
    userId: user.id,
    notificationSent: user.status === 'active',
    logId: logResult.id,
  };
}

Now define the activities that do the actual work in src/activities.ts:

import axios from 'axios';

interface StripeUser {
  id: string;
  email: string;
  status: string;
  subscriptions: Array<{ id: string; status: string }>;
}

interface SlackPayload {
  channel: string;
  message: string;
}

interface DatabaseLog {
  customerId: string;
  status: string;
  timestamp: string;
}

interface LogResult {
  id: string;
}

export async function fetchUserFromStripe(customerId: string): Promise<StripeUser> {
  const response = await axios.get(`https://api.stripe.com/v1/customers/${customerId}`, {
    headers: {
      Authorization: `Bearer ${process.env.STRIPE_API_KEY}`,
    },
  });

  const subscriptions = await axios.get(
    `https://api.stripe.com/v1/customers/${customerId}/subscriptions`,
    {
      headers: {
        Authorization: `Bearer ${process.env.STRIPE_API_KEY}`,
      },
    }
  );

  return {
    id: response.data.id,
    email: response.data.email,
    status: response.data.description || 'unknown',
    subscriptions: subscriptions.data.data,
  };
}

export async function sendSlackNotification(payload: SlackPayload): Promise<void> {
  await axios.post(process.env.SLACK_WEBHOOK_URL, {
    channel: payload.channel,
    text: payload.message,
    ts: Math.floor(Date.now() / 1000),
  });
}

export async function logToDatabase(log: DatabaseLog): Promise<LogResult> {
  const response = await axios.post(process.env.DATABASE_WEBHOOK_URL, {
    customerId: log.customerId,
    status: log.status,
    timestamp: log.timestamp,
  });

  return { id: response.data.insertedId };
}

Create a worker in src/worker.ts:

import { Worker } from '@temporalio/worker';
import * as workflows from './workflows';
import * as activities from './activities';

async function runWorker() {
  const worker = await Worker.create({
    workflowsPath: require.resolve('./workflows'),
    activitiesPath: require.resolve('./activities'),
    taskQueue: 'stripe-webhook-queue',
    namespace: 'default',
    workflowFailureExceptionTypes: [Error],
  });

  console.log('Temporal Worker started, listening on queue: stripe-webhook-queue');
  await worker.run();
}

runWorker().catch(console.error);

Finally, trigger a workflow execution in src/run-workflow.ts:

import { Connection, Client } from '@temporalio/client';
import { processStripeWebhook } from './workflows';

async function runWorkflow() {
  const connection = await Connection.connect({ address: 'localhost:7233' });
  const client = new Client({ connection });

  const workflowId = `stripe-webhook-${Date.now()}`;

  const result = await client.workflow.execute(processStripeWebhook, {
    args: ['cus_abc123xyz'],
    taskQueue: 'stripe-webhook-queue',
    workflowId,
  });

  console.log('Workflow completed:', result);
}

runWorkflow().catch(console.error);

Start your worker:

npm run worker

In another terminal, run the workflow:

npm run workflow

You'll see the workflow execute across all three activities: fetch from Stripe, send a Slack message, and log to your database. If any step fails, Temporal retries it automatically. That's the power of durable execution.

Make: The Visual No-Code Platform

Now let's build the exact same workflow in Make.com—the visual way.

Make is cloud-hosted, which means zero infrastructure overhead. You log in, drag modules onto a canvas, and connect them. Each module represents an API call or data transformation. No code required, though you can add JavaScript when needed.

The tradeoff? You pay per operation. Make charges based on the number of "operations" (API calls and data transformations) your workflows perform. If you're running 10,000 Stripe API calls per month, costs add up quickly.

Here's how to replicate the Temporal workflow in Make:

1. Log into Make and create a new scenario.

2. Set up the trigger. Add a Webhook module as your trigger. This gives you a webhook URL that Stripe can POST to when events occur.
   

Make → Webhook → Listen on this URL for Stripe webhook events

1. Parse the webhook. Add a JSON → Parse JSON module to extract the customerId:

{
  "customerId": "{{trigger.body.data.object.customer}}"
}

1. Fetch from Stripe. Add a Stripe module (or use HTTP Request):

Module: HTTP → Make a request

• URL: https://api.stripe.com/v1/customers/{{customerId}}
• Method: GET
• Headers: Authorization: Bearer {{env.STRIPE_API_KEY}}

1. Conditional routing. Add a Router to check if status == 'active':

Router → if status = "active"
  → YES: Send Slack notification
  → NO: Skip notification

1. Send to Slack. In the YES path, add a Slack module:

• Message: User {{firstName}} {{lastName}} ({{email}}) is active with {{subscriptionCount}} subscriptions
• Channel: #billing

1. Log to database. Add an HTTP Request module:

• URL: {{env.DATABASE_WEBHOOK_URL}}
• Method: POST
• Body:

{
  "customerId": "{{customerId}}",
  "status": "{{stripeResponse.status}}",
  "timestamp": "{{now()}}"

Originally published on Automation Insider.