n8n vs Make for scraping workflows
Choose n8n when you want to self-host, keep credentials on your own server and write code in the flow; choose Make when you want a hosted service with visual modules and no server to run. For a scraping job such as the Google Maps leads to Google Sheets workflow linked here, the hosted Actor does the extraction either way, and the platform only schedules it and moves the rows.
Checked 2026-11-12
Do it now
The workflow from Google Maps leads to Google Sheets, ready to import into n8n: Google Maps Business Lead Finder with Email & Social Links on Apify, then Google Sheets.
n8n workflowgoogle-maps-leads-to-google-sheets.n8n.json
{
"name": "Google Maps leads to Google Sheets",
"nodes": [
{
"id": "509d4612-2b8a-4dc6-ab8a-c397f93c9eeb",
"name": "Run by hand",
"type": "n8n-nodes-base.manualTrigger",
"typeVersion": 1,
"position": [
0,
0
],
"parameters": {}
},
{
"id": "4eee49e2-88cd-4154-a73d-aae1a912e03b",
"name": "Every day",
"type": "n8n-nodes-base.scheduleTrigger",
"typeVersion": 1.2,
"position": [
0,
200
],
"parameters": {
"rule": {
"interval": [
{
"triggerAtHour": 8
}
]
}
},
"notes": "Activate the workflow to run on this schedule."
},
{
"id": "c5045336-dcd8-4d61-af73-5330168f04f3",
"name": "Run Apify Actor",
"type": "n8n-nodes-base.httpRequest",
"typeVersion": 4.2,
"position": [
260,
100
],
"parameters": {
"method": "POST",
"url": "https://api.apify.com/v2/actors/vexaloom-labs~google-maps-business-lead-finder-with-email/run-sync-get-dataset-items",
"authentication": "genericCredentialType",
"genericAuthType": "httpHeaderAuth",
"sendBody": true,
"specifyBody": "json",
"jsonBody": "{\n \"mode\": \"searchPlaces\",\n \"searchQueries\": [\n \"coffee shops in Austin TX\"\n ],\n \"maxPlacesPerSearch\": 20,\n \"language\": \"en\",\n \"extractEmailsFromWebsite\": true,\n \"maxEmailsPerWebsite\": 5,\n \"maxContactPagesPerWebsite\": 2,\n \"onlySaveResults\": \"allPlaces\",\n \"websiteFilter\": \"allPlaces\",\n \"skipClosedPlaces\": false\n}",
"options": {
"timeout": 310000
}
},
"notes": "Actor: vexaloom-labs/google-maps-business-lead-finder-with-email. Select a Header Auth credential: name Authorization, value Bearer + your Apify token. Edit the JSON body to change the input.",
"notesInFlow": false
},
{
"id": "04208c8a-673c-4326-aa3d-8e4f02a3c86b",
"name": "Only records not sent before",
"type": "n8n-nodes-base.removeDuplicates",
"typeVersion": 2,
"position": [
500,
100
],
"parameters": {
"operation": "removeItemsSeenInPreviousExecutions",
"logic": "removeItemsWithAlreadySeenKeyValues",
"dedupeValue": "={{ $json.placeId }}",
"options": {
"scope": "node",
"historySize": 10000
}
},
"notes": "Remembers each placeId it has passed on (up to 10,000) across runs, so a record is sent once. Needs n8n 1.64 or later."
},
{
"id": "7e87da9a-fac8-48b8-a610-f389e9ae0b07",
"name": "Keep main fields",
"type": "n8n-nodes-base.code",
"typeVersion": 2,
"position": [
740,
100
],
"parameters": {
"jsCode": "// Keeps the Actor's main fields as flat, spreadsheet-safe values.\nconst columns = [\"title\",\"address\",\"totalScore\",\"reviewsCount\",\"website\",\"sourceUrl\",\"contactPageUrl\",\"url\",\"placeId\",\"searchQuery\",\"categoryName\",\"phone\",\"emails\",\"emailsMxValid\"];\n// A dotted name such as author.name reads the nested value.\nconst read = (obj, key) => (key in obj ? obj[key] : key.split('.').reduce((v, part) => (v && typeof v === 'object' ? v[part] : undefined), obj));\nreturn $input.all().map((item) => {\n const row = {};\n const present = columns.filter((key) => read(item.json, key) !== undefined);\n // A record shaped differently from the published schema keeps its own fields rather than arriving blank.\n for (const key of present.length >= 2 ? present : Object.keys(item.json)) {\n const value = read(item.json, key);\n row[key] = value === null || value === undefined ? '' : typeof value === 'object' ? JSON.stringify(value) : value;\n }\n return { json: row };\n});"
}
},
{
"id": "caff81da-6e9f-46e4-ae58-03b1f27a7723",
"name": "Send to Google Sheets",
"type": "n8n-nodes-base.googleSheets",
"typeVersion": 4.5,
"position": [
980,
100
],
"parameters": {
"operation": "append",
"documentId": {
"__rl": true,
"value": "",
"mode": "list",
"cachedResultName": ""
},
"sheetName": {
"__rl": true,
"value": "Sheet1",
"mode": "name"
},
"columns": {
"mappingMode": "autoMapInputData",
"value": {},
"matchingColumns": [],
"schema": []
},
"options": {}
},
"notes": "Pick your spreadsheet. The tab is set to Sheet1; change it if yours has another name. Add these headers in row 1: title, address, totalScore, reviewsCount, website, sourceUrl, contactPageUrl, url, placeId, searchQuery, categoryName, phone, emails, emailsMxValid."
},
{
"id": "6fec453a-ccdd-49f0-a12f-b5117bf71fa7",
"name": "Setup",
"type": "n8n-nodes-base.stickyNote",
"typeVersion": 1,
"position": [
0,
-370
],
"parameters": {
"content": "## Google Maps Business Lead Finder with Email & Social Links\n\nSource: [vexaloom-labs/google-maps-business-lead-finder-with-email](https://apify.com/vexaloom-labs/google-maps-business-lead-finder-with-email) on Apify.\n\n1. In **Run Apify Actor**, create a Header Auth credential: name `Authorization`, value `Bearer YOUR_APIFY_TOKEN` with your token.\n2. Open **Send to Google Sheets** and connect your Google Sheets account.\n3. Edit the JSON body of **Run Apify Actor** to change the input.\n\nGenerated by recipeforagents.com. Validated, not executed: runs are billed to your Apify account.",
"height": 340,
"width": 460,
"color": 6
}
}
],
"connections": {
"Run by hand": {
"main": [
[
{
"node": "Run Apify Actor",
"type": "main",
"index": 0
}
]
]
},
"Every day": {
"main": [
[
{
"node": "Run Apify Actor",
"type": "main",
"index": 0
}
]
]
},
"Run Apify Actor": {
"main": [
[
{
"node": "Only records not sent before",
"type": "main",
"index": 0
}
]
]
},
"Only records not sent before": {
"main": [
[
{
"node": "Keep main fields",
"type": "main",
"index": 0
}
]
]
},
"Keep main fields": {
"main": [
[
{
"node": "Send to Google Sheets",
"type": "main",
"index": 0
}
]
]
}
},
"pinData": {},
"active": false,
"settings": {
"executionOrder": "v1"
},
"meta": {
"templateCredsSetupCompleted": false
},
"tags": []
} Validated, not executed: 11 of 11 checks pass
- It has a nodes array and a connections object
- Every node has a name, type, typeVersion, position and parameters
- Node names are unique
- Every node type is a known n8n core node (or the Apify node)
- Every node uses a typeVersion that n8n ships
- Every connection points at an existing node
- At least one trigger starts the workflow
- Every working node is reachable from a trigger
- Apify calls use POST and a credential for the token
- Actor input matches the Actor's published input schema
- No token or credential value is embedded
The deciding question is where the schedule, the credentials and the data volume live. n8n is self-hostable workflow automation with native HTTP and code nodes; Make is hosted automation with visual modules and scenario runs. Both can call Apify's API with an HTTP step, so the scraper itself does not tie you to either.
What you need
- An Apify token, stored as a credential in either tool and never in the request body.
- A clear job definition: the input, the expected fields, the schedule and the destination.
- For n8n: n8n Cloud or a server you maintain. For Make: a Make account and a plan with enough scenario runs for your schedule.
- Someone who owns failures: a broken credential or a changed sheet header stops either platform.
Where it breaks
Volume is the usual surprise. A daily scrape that returns hundreds of rows becomes hundreds of module operations in a hosted per-operation plan, while a self-hosted n8n instance only costs its server. On the other side, self-hosting means you patch, back up and monitor n8n yourself. Write the run frequency and row count down before you pick.
Method
Write down the scrape's input, the fields you need, how often it runs and where the rows go, using the Google Maps leads to Google Sheets workflow as the reference job.
Decide who maintains the platform: if nobody will run a server, start with a hosted service; if data must stay on your infrastructure, self-host n8n.
Rebuild the same job in the other tool with one HTTP step to Apify's synchronous run endpoint, a Bearer token credential and the sheet step.
Run both by hand for a week of typical volume and compare failures, run time and the operations or executions each platform counted.
Ready-made recipe
Google Maps leads to Google Sheets: an n8n workflow you can import, using Google Maps Business Lead Finder with Email & Social Links.
Troubleshooting
Why does the workflow or script stop with HTTP 408?
The synchronous endpoint waits at most 300 seconds. After that it answers 408 while the run keeps going in Apify. Lower the result limit, or start the run asynchronously, wait for it to finish and then read its dataset.
Source: Apify API: run Actor synchronously and get dataset items
What do 400, 401, 402 and 403 from the Apify API mean?
Read error.type in the response body. 400 is invalid Actor input. 401 (user-or-token-not-found) means a token reached Apify but it is wrong or revoked. 402 with x402-payment-required means no token reached Apify at all: the n8n credential or the Authorization: Bearer header is missing, and Apify is offering its pay-per-run x402 route for agents instead; any other 402 is an exhausted usage limit on the account that pays for the run. 403 is a token without permission for that Actor or storage.
Source: Apify API: authentication; Apify documentation: agentic payments with x402; Apify API: run Actor synchronously and get dataset items
n8n says Install this node to use it after import. Why?
The workflow names a node or node version your instance does not have, usually a community node. The workflows here use only built-in nodes at versions n8n has shipped since 1.80, so they import on n8n Cloud and older self-hosted instances without community nodes.
Why does the HTTP Request node time out before Apify answers?
Set the node's Timeout option to at least 300000 ms so n8n waits as long as Apify's synchronous endpoint. The workflows here already set 310000. A failure at exactly 30 seconds points to a proxy in front of n8n.
Why does starting an Actor through the API return run information instead of scraped results?
The Run Actor endpoint starts the Actor and immediately returns a Run object without waiting for completion. For results stored in the default dataset, pass the response's defaultDatasetId to Get dataset items; to wait and receive output directly, use the synchronous endpoint for dataset items or a key-value store record.
Source: Apify Run Actor API
Questions
Can Make call Apify Actors?
Yes. Make has an HTTP module and an Apify app, so it can start an Actor and read its dataset the same way n8n does.
Is n8n free to self-host?
The self-hosted community edition has no licence fee for internal use, but you pay for the server and the time to run it.
Which handles errors better?
Both can retry and route errors. n8n lets you add code and error workflows on your own server; Make keeps error handling in its hosted scenario editor.
Does the choice change the scraped data?
No. The Actor returns the same fields to either platform; the choice only changes scheduling, credentials and where the rows travel.