Google Maps Scraper Alternative: Local Business Leads from Open Data

What it does

Most local lead lists start with a Google Maps scraper, and most of the pain comes with it: blocked requests, proxies, CAPTCHAs and a results list that stops at around 120 places per search. If what you actually need is names, addresses, phone numbers and websites for every dentist in Austin or every restaurant in Berlin, you do not need Google at all.

Business Places Data reads the Overture Maps Foundation places dataset, an open GeoParquet release of 80M+ business points of interest refreshed monthly and built from Meta, Microsoft, Foursquare, AllThePlaces, BrightQuery and other sources. Nothing is scraped, so a whole city comes back in seconds. Each row carries the business name, category, full address, latitude/longitude, E.164 phone numbers, website, business email, social links and brand, plus a plain Google Maps search link.

It is built for agencies, SDR teams and data people who want permissive, resellable lead data. Every row lists its sources, licence and attribution, and the licences (CDLA-Permissive-2.0, Apache-2.0, CC0) are not share-alike, so you may store, enrich and resell the leads as long as attribution travels with them. The trade-off is honest: this is not Google data, so there are no reviews, star ratings, opening hours or photos.

How it works

1. You give a city name (32,000+ cities are built in), a bounding box, or a lat/lon centre with a radius, plus optional categories such as dentist or plumber.
2. The actor finds the newest monthly Overture release and reads only the GeoParquet row groups that overlap your area, typically 15-45 MB for a city.
3. Places are filtered by category (2,100+ Overture ids, with plain-word synonyms), name, confidence and whether they have a website, phone or email.
4. Phones are normalised to E.164, possibly personal emails are removed, and each row is written with its sources, licence and attribution.
5. Results are ordered by confidence (or by distance for a radius search) and the run stops at your maxPlaces cap or spend limit.

Input example

A typical run input (JSON). Every field is also available as a form in the Apify console.

{
  "location": "Austin, TX",
  "categories": [
    "dentist"
  ],
  "maxPlaces": 200,
  "minConfidence": 0.5,
  "requireWebsite": true,
  "countryCode": "US"
}

Output example

A run for dentists in Austin, TX returns rows like these, one per place, with contacts and licence on every row:

Pricing

Pay per event: you are charged only for the results you receive, with no subscription. Set a maximum total charge on any run and it stops cleanly at the cap.

Prices are read from the live Apify Store listing when this page is built. The listing is always authoritative.

Use cases

How it compares

If you need Google reviews, star ratings, opening hours or same-day freshness, a Google Maps scraper is the better tool. If you need contactable business rows at city scale with a clear licence, open data is cheaper and does not break.

Limits and honest notes

• Open data, not Google: no reviews, ratings, review counts, opening hours, photos, popular times or price levels. The Google Maps link in each row is a plain search URL built from the name and address; nothing is fetched from Google.
• Freshness follows Overture's monthly releases. The newest release is found automatically (or pin one with release). operatingStatus is often empty, so a closed business can still appear until a source drops it; minConfidence (default 0.5) filters most stale records.
• Coverage varies by country and category. In the test cities almost every dentist and restaurant had a phone and a website; emails were present for about 75% of Austin dentists but about 32% of Berlin restaurants. Rural areas and parts of Africa and Asia are thinner.
• Categories are Overture's taxonomy (2,100+ ids such as dental_clinic or italian_restaurant). Common plain words are mapped for you; run listCategories (free) to browse the rest.
• One query per run, up to 1.5 x 1.5 degrees (about one metro area). For a region or country, run once per city. A city query typically reads 15-45 MB of public GeoParquet in 5-15 seconds at 1 GB memory.
• Business contacts only: phones, emails and socials are the business's published contacts. Free-mail addresses that do not contain the business name and off-domain personal-looking addresses are removed (counted in droppedPersonalEmails). You remain responsible for how you use the data under GDPR, CAN-SPAM and similar laws.
• City names resolve offline from a built-in list of 32,000+ cities (Overture divisions, OpenStreetMap-based); smaller towns are looked up in Overture's divisions data and need a region or country ("Dripping Springs, TX"). No external geocoder is called.
• The run's spend limit is respected: the area query is reserved first, places are charged before delivery, and the run stops cleanly at the limit.

Data licence and attribution

Places come from the Overture Maps Foundation places theme. Each row's sources lists the contributing datasets with their record ids, licence and licenceUrls give the licences, and attribution holds the required credit lines. If you republish the data, keep the attribution field (or show the lines below).

- © Overture Maps Foundation, overturemaps.org - Meta, Microsoft, PinMeTo, Krick, RenderSEO, DAC, BrightQuery: "Data from <source>. Available under CDLA Permissive 2.0." (CDLA-Permissive-2.0) - Foursquare: "Copyright 2024 Foursquare Labs, Inc. All rights reserved. Available under Apache 2.0. Foursquare data was transformed to the Overture schema. Changed: 2026-03-18." (Apache-2.0) - AllThePlaces: "Data from AllThePlaces. Available under CC0 1.0."

None of these licences is share-alike, so the rows may be used commercially, stored, merged with your own data and redistributed, provided the attribution and licence texts travel with them.

City boundaries used to turn a city name into a search area come from the Overture divisions theme: © OpenStreetMap contributors, Overture Maps Foundation, available under the Open Database License (ODbL) 1.0. They are used only for the search area and are not part of the output rows. The built-in city list is a derivative database offered under the ODbL; it is rebuilt from the public Overture release by a documented query.

Changes made by this actor: rows are selected by area, category, name and confidence; fields are flattened and renamed; phone numbers are normalised to E.164; possibly personal emails are removed.

Foursquare OS Places NOTICE (preserved in full, as Apache-2.0 requires; also included in the run's OUTPUT record whenever Foursquare rows are delivered):

> © 2026 Foursquare Labs, Inc. All rights reserved. > > The Foursquare OS Places dataset (the "Data") is licensed under the Apache License, Version 2.0 (the "License"). You may not use, modify, or distribute the Data except in compliance with the License. > > As set forth more fully in the License, if you use, modify, or distribute the Data, you must: provide recipients with a copy of the License; if applicable, include prominent notices to the extent you've changed the Data; preserve attribution to Foursquare, including preserving the full content of this NOTICE.txt file. > > To ensure appropriate attribution to Foursquare, we recommend the following: if using/distributing the Data in flat file form as-is or after making changes/modifications: include this NOTICE.txt file, which may be modified to include an additional notice of your changes/modifications, if any; if using/distributing the Data in API form as-is or after making changes/modifications: include a copy of the content from this NOTICE.txt file prominently in your developer documentation for such API, which may be modified to include an additional notice of your changes/modifications, if any. > > You may obtain a copy of the License at: http://www.apache.org/licenses/LICENSE-2.0. Unless required by applicable law or agreed to in writing, the Data distributed under the License is distributed on an "AS IS" BASIS, WITHOUT WARRANTIES OR CONDITIONS OF ANY KIND, either express or implied. See the License for the specific language governing permissions and limitations under the License.

This actor is not affiliated with, endorsed by or sponsored by Google, the Overture Maps Foundation or any data contributor. "Google Maps" is a trademark of Google LLC and is used only to describe what this actor is an alternative to.

FAQ

Use it from code

Run the actor through the Apify API with the input above.

cURL

curl -X POST "https://api.apify.com/v2/acts/actor-forge~business-places-data/run-sync-get-dataset-items" \
  -H "Authorization: Bearer $APIFY_TOKEN" \
  -H "Content-Type: application/json" \
  -d '{"location": "Austin, TX", "categories": ["dentist"], "maxPlaces": 200, "minConfidence": 0.5, "requireWebsite": true, "countryCode": "US"}'

JavaScript (Node.js)

// Node.js 18+ (built-in fetch). Set APIFY_TOKEN in your environment.
const input = {
  "location": "Austin, TX",
  "categories": [
    "dentist"
  ],
  "maxPlaces": 200,
  "minConfidence": 0.5,
  "requireWebsite": true,
  "countryCode": "US"
};

const res = await fetch(
  "https://api.apify.com/v2/acts/actor-forge~business-places-data/run-sync-get-dataset-items",
  {
    method: "POST",
    headers: {
      Authorization: `Bearer ${process.env.APIFY_TOKEN}`,
      "Content-Type": "application/json",
    },
    body: JSON.stringify(input),
  }
);
const items = await res.json();
console.log(items.length, items[0]);

Python

# pip install apify-client   (set APIFY_TOKEN in your environment)
import os
from apify_client import ApifyClient

client = ApifyClient(os.environ["APIFY_TOKEN"])
run_input = {
    "location": "Austin, TX",
    "categories": [
        "dentist"
    ],
    "maxPlaces": 200,
    "minConfidence": 0.5,
    "requireWebsite": True,
    "countryCode": "US"
}

run = client.actor("actor-forge/business-places-data").call(run_input=run_input)
for item in client.dataset(run["defaultDatasetId"]).iterate_items():
    print(item)

The run-sync-get-dataset-items endpoint waits for the run (up to 5 minutes) and returns the dataset rows directly. For longer runs, start the run asynchronously and read the dataset when it finishes, as the Python example does. Replace APIFY_TOKEN with your own token from the Apify console.

Step-by-step guides

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