Good Google Maps data comes down to a few plain things. How many listings you get per area. Whether reviews arrive in the same account as listings. How fresh the data is. And who fixes things when the page structure changes. The trap: a tool that looks cheap per request but leaves your team maintaining parsers, proxies and retry logic. You pick on the demo, then pay for it in engineering hours.
Teams buying a Google Maps data API usually track local rankings across many client locations, feed a reputation product, or build lead lists. Each needs a different shape of data. I judged every option below on geographic coverage, result depth, review access, freshness, pricing model and maintenance burden.
The table below is a quick orientation before the entries.
| Provider | Best for | Pricing |
| DataForSEO | Developers, growth teams, local SEO agencies | mid-range, pay-as-you-go |
| Scrapingdog | Developers wanting a simple Maps endpoint | accessible, subscription |
| HasData | Pipelines with no-code options | accessible, subscription |
| Bright Data | Large enterprise data programs | premium, subscription |
| Outscraper | Fast one-off Maps and review exports | accessible, pay-as-you-go |
| Oxylabs | Enterprise teams already on proxies | premium, subscription |
| Apify | Teams assembling custom scraper workflows | mid-range, subscription + usage |
| Scrape.do | Teams wanting a Maps API with lean billing | accessible, subscription |
How the list was built
I reviewed eight providers, drawing on public documentation, endpoint lists, output formats, integrations and pricing models. Where a free tier or sample call existed, I looked at what the response actually contains. I did not run a benchmark across them, so I make no speed or accuracy claims.
Filters were practical. A provider stayed in only if Google Maps listing data was a documented product, not a side effect of a generic proxy pool. Review access had to be clear, either inside the same product or through a stated separate route. Pricing had to be understandable without a sales call to know the model.
I also read user reviews on Trustpilot and G2, looking for patterns around support responsiveness, onboarding friction and reliability complaints that documentation never mentions. I treated the scores themselves as a secondary signal, not a verdict.
What separates one Maps API from another
Depth per area
Some APIs return a page of results per query. Others return hundreds of listings for a defined area. For rank tracking and lead lists, depth decides whether you need one request or fifty.
Location precision
City-level targeting is common. Region, district and custom-drawn areas are rarer. Agencies tracking rankings from specific neighborhoods feel this gap fast.
Reviews and profile data
Listings alone do not cover reputation work. Check whether review collection sits in the same account, covers any language, and how it is delivered: live or scheduled.
Who maintains collection
A scraper you run yourself breaks when layouts shift. A managed API moves that cost to the vendor. Ask who handles blocking, parser updates and retries.
Integrations
Connectors for n8n, Make, Zapier and Google Sheets decide whether a non-developer can pull data without a ticket.
How they compare
| Company | Trustpilot | G2 |
| Scrapingdog | 4.6/5 | 3/5 |
| HasData | 4.5/5 | 4.8/5 |
| Bright Data | 4.3/5 | 4.7/5 |
| Outscraper | 4.6/5 | 3.9/5 |
| Oxylabs | 3.9/5 | 4.5/5 |
| Apify | 4.8/5 | 4.7/5 |
| Scrape.do | 4.8/5 | 5/5 |
| DataForSEO | 4.5/5 | 4.4/5 |
The 8 providers
1. DataForSEO
Local SEO agencies and tool builders get the most complete fit here. A single Google Maps SERP API call can pull as many as 700 business listings for one area, each with its address, review score and opening hours. Targeting goes down to regions and districts, or to a custom shape drawn on the map.
Results arrive in seconds in live mode, while queues take care of large batches. DataForSEO runs the collection itself, so your team skips proxy and parser upkeep.
Reputation work stays in the same account. The Business Data API adds Google Business Profile information and Google Reviews from any location in any language, alongside Trustpilot, Tripadvisor and Google Hotels data. Reviews and profile data come mainly through a task queue, which suits scheduled pulls better than instant lookups.
As a Google Maps data API, DataForSEO serves agencies tracking map rankings across many client locations. An MCP server covers Claude, Cursor and ChatGPT, and connectors reach n8n, Make, Zapier and Google Sheets. On Trustpilot it shows 4.5/5 from 66 reviews.
Best for: developers, growth teams, local SEO agencies and tool makers building on a Google Maps data API across many locations
2. Scrapingdog
Reviews live on their own endpoint here, which tells you how the product is organized. The Google Maps API returns business names, addresses, hours, phone numbers, ratings and review counts, while review text is fetched separately.
The company was started in 2021 by Manthan Koolwal, with Darshan Khandelwal as co-founder and CTO; the website went live in April 2020. That is a young operation, and it shows in a lean, developer-first product surface.
On Trustpilot it scores 4.6/5 across 552 reviews. G2 is thinner: 3/5 from 4 reviews, too few to read much into.
Best for: developers who want a straightforward Maps listing endpoint and can handle reviews as a second call
3. HasData
Two ways in: code or no code. HasData offers a Google Maps Search API and a no-code Google Maps Scraper, part of a catalog of 63 API endpoints and 21 no-code scrapers aimed at data pipelines and AI workloads.
The company says it is trusted by 1.3k+ customers and charges only for successful requests, which matters when blocked calls would otherwise eat budget.
On G2 it sits at 4.8/5, and on Trustpilot at 4.5/5.
A marketing analyst can export a list without engineering help, and a developer can wire the same data into a pipeline.
Best for: mixed teams where analysts need no-code exports and engineers need an API
4. Bright Data
Scale is the pitch. Bright Data was founded in 2014 and was formerly named Luminati Networks, so its roots are in proxy infrastructure. Today it sells proxy networks, AI-powered scraping tools and refreshed datasets.
It states that it serves more than 50,000 customers and has over 600 team members. That size brings enterprise procurement, compliance paperwork and account management.
G2 shows 4.7/5 from 318 reviews. Trustpilot shows 4.3/5 from 998 reviews.
As a premium, subscription-based vendor, it suits organizations that already run large data programs and want one provider for proxies, scrapers and datasets.
Best for: enterprise data teams consolidating proxies, scraping tools and ready datasets under one contract
5. Outscraper
A Google Maps Scraper and a Google Maps Reviews Scraper lead the catalog, so Maps data is the core business rather than a feature. Outscraper is based in Bee Cave, Texas.
Beyond Maps, it covers emails and contacts, Google Search, Amazon, Tripadvisor, Trustpilot and Yellow Pages, with a family of APIs behind the scrapers. That breadth helps when a lead-gen project needs contact enrichment next to listings.
Ratings: 4.6/5 on Trustpilot, 3.9/5 on G2.
Best for: growth teams exporting Maps listings and reviews for lead lists or one-off research
6. Oxylabs
Proxy muscle first, scrapers second. Oxylabs was founded in 2015 in Vilnius, Lithuania, and reports 15,000+ clients, 500+ employees and a pool of 177M+ proxies. In 2022 it acquired the self-service proxy platform Webshare.
That infrastructure sits underneath its scraping products, which appeals to teams that care about network reach and already buy proxies.
G2 shows 4.5/5; Trustpilot shows 3.9/5.
Best for: enterprise teams that already depend on proxy infrastructure and want scraping from the same vendor
7. Apify
An app store for scrapers. Apify launched in 2015, founded by Jan Čurn and Jakub Balada out of the Y Combinator Fellowship, and is built in Prague. Its Apify Store lists more than 100,000 ready-made scrapers called Actors.
It also maintains Crawlee, a scraping and crawling library, and reports 91,000 customers. An MCP server gives AI agents access to Actors.
Ratings are strong: 4.8/5 on Trustpilot and 4.7/5 on G2. Billing mixes a subscription with usage, at a mid-range tier.
With 100,000+ Actors in the Store, teams pick and configure their own scraper rather than adopt a single fixed product.
Best for: technical teams that want to combine and customize scrapers inside one platform
8. Scrape.do
Request volume is the headline. Scrape.do, run by PACKEND, LLC, states 10B+ requests a month and a pool of 150 million proxies. Its ready-made scraper APIs cover Google Maps, Search, Shopping, Hotels, News and Trends.
It charges only for successful requests, a fair model for blocked-heavy targets.
Scores look excellent: 5/5 on G2 from 4 reviews and 4.8/5 on Trustpilot from 64 reviews. The G2 sample is tiny, so lean on Trustpilot’s larger base.
Best for: teams wanting a Maps scraper API inside a wider Google data toolkit with success-only billing
Questions to settle before you commit
Run these against any Google Maps data API you are considering.
1. How many listings come back per area? Depth decides whether a district-level rank check is one call or dozens. Ask every vendor for the exact ceiling per area and what happens beyond it.
2. Are reviews live or queued? Scheduled collection suits reputation dashboards. Instant lookups need a different route. Scrapingdog separates reviews into their own endpoint, and Outscraper makes reviews a headline scraper.
3. Who fixes parser breaks? A managed API like Scrape.do or HasData pushes this to the vendor. A store of community scrapers, as on Apify, may not.
4. Does the billing model match your volume curve? Pay-as-you-go suits irregular pulls; subscriptions suit steady use. Bright Data and Oxylabs fit organizations already budgeting that way.
5. Can non-developers pull data? Connectors for Sheets, n8n or Make, and no-code scrapers, decide whether analysts depend on engineering.
Your answer to the first question usually narrows the field faster than any rating.
Frequently Asked Questions
How does pricing work for a Google Maps data API?
Models fall into pay-as-you-go, subscription, and subscription plus usage. Pay-as-you-go suits irregular pulls, while subscriptions suit steady volume. Some vendors charge only for successful requests. Check minimum top-ups and whether reviews are billed separately from listings.
How do I compare a Google Maps data API for local SEO?
Compare results per area, location precision, review access and who maintains collection. Agencies tracking many client locations care most about district-level targeting and bulk queues. Integration options such as n8n, Make or Google Sheets also affect how quickly a team gets value.
What does a Google Maps data API return?
Typically business name, address, phone, working hours, rating and review count. Some products return review text through a separate endpoint or a task queue. Google Business Profile details may sit in a different product, so confirm the exact fields before integrating.
How long does it take to set up a Google Maps data API?
Setup time depends on the integration route and the volume you need. A direct REST call, a connector in Sheets or Make, and a bulk review pipeline each take different effort. Multi-location rank tracking adds scheduling and storage design on top.
Is a Google Maps data API worth it for a small team?
It pays off once you track more than a handful of locations or refresh data regularly. Pay-as-you-go options keep entry costs low for small teams. A single manual check of one listing does not need an API.
