The best Google Maps scraper depends on the job. A sales analyst exporting leads to CSV has a different problem from a developer using the Google Maps Places API, a growth team scheduling Outscraper jobs, or an engineer comparing google maps scraper GitHub projects. This guide shows where UScraper's Google Maps Leads Scraper by Keywords fits.
Comparison frame
What Google Maps scraper alternatives really differ on
Most Google Maps scraper alternatives can collect business name, rating, reviews, address, phone, website, category, coordinates, and hours. The durable differences show up after the first run: hosting, output custody, pricing meter, code requirement, and selector maintenance.
Searches like how to scrape Google Maps leads, outscraper alternative, and apify vs octoparse google maps usually mix four approaches:
- Official APIs for approved app integrations.
- Hosted scraping platforms such as Apify, Outscraper, Octoparse, PhantomBuster, Bright Data, SerpApi, and DataForSEO.
- Open-source or custom scripts where engineering owns proxies, parsing, retries, and storage.
- Local desktop app workflows such as UScraper templates, where the operator inspects the browser flow and exports CSV locally.
The practical question is not "can this tool scrape Google Maps?" It is "which workflow gives us rows we can audit, afford, maintain, and use legally?"
Side-by-side
Google Maps scraper alternatives compared
| Option | Best fit | Hosting | Code needed | Output shape | Pricing shape | Main trade-off |
|---|---|---|---|---|---|---|
| Google Places API | Approved app workflows, product features, and structured place lookup | Google Cloud | Medium | JSON from Text Search or Place Details | API usage and billing | Strongest governance route, but not a spreadsheet scraper |
| Apify Google Maps actors | Hosted scraping runs, datasets, webhooks, and API-driven automation | Apify cloud | Low to medium | Dataset, JSON, CSV, Excel | Platform and actor usage | Strong automation, but data runs through a cloud actor workflow |
| Octoparse Google Maps templates | No-code teams that want visual setup and cloud tasks | Vendor platform | Low | Table exports, CSV, Excel | SaaS plan and task limits | Easy no-code setup, less local custody |
| Outscraper | Teams wanting Google Maps scraping as a no-code service or API | Vendor cloud | Low to medium | CSV, Excel, JSON, API delivery | Usage, plan, or API pricing | Convenient managed service, but vendor-hosted |
| PhantomBuster | Sales ops workflows and spreadsheet-connected automations | Vendor cloud | Low | CSV or Google Sheets-friendly exports | Plan and automation limits | Useful for growth workflows, less suited to local QA |
| SerpApi, Bright Data, DataForSEO | API-first SERP and Maps data pipelines | Vendor infrastructure | Medium | JSON or delivered files | Request, result, or contract pricing | Powerful for developers, heavy for one analyst CSV |
| Open-source scripts | Engineering teams that want full parser ownership | Your environment | High | Whatever you build | Engineering time plus infrastructure | Maximum control, maximum maintenance |
| UScraper + Google Maps Leads Scraper by Keywords | Analyst-led lead exports from known place URLs | Local desktop app | Low | CSV: place details and lead fields | Free template; app licensing applies | Best for inspectable local runs, not cloud-scale pipelines |
This is not a universal ranking. A data product should start with an API route. A local SEO analyst may care more about a readable CSV and a workflow they can watch.
Where UScraper wins
When a local desktop app scraper is the better fit
UScraper wins when the job is local, visual, and CSV-first. The related Google Maps Leads Scraper by Keywords template opens configured Google Maps place URLs, waits for each detail page, exports columns, then continues through the URL list. The template is free to import; UScraper app licensing applies for real usage.
That model fits keyword and location lists such as "dentists in Miami", "coffee shops in Austin", or "roofing companies near Denver". Instead of treating the scraper as an opaque API call, the operator can see the browser flow:
Set Window Size -> Navigate URL list -> Wait for Page Load
-> Sleep -> Wait for h1 -> Structured Export -> Loop Continue
The bundled workflow exports lead fields such as name, reviews, rating, address, website, phone, hours, page URL, identifiers, coordinates, category, images, status, plus code, weekday hours, and popular-times columns when visible.
| UScraper advantage | Why it matters for Google Maps leads |
|---|---|
| Local desktop app flow | The browser steps and CSV save path are visible to the operator. |
| Visual blocks | Navigation, waits, selectors, export columns, and loops can be inspected. |
| CSV-first output | Teams can review leads in spreadsheets before CRM import or enrichment. |
| Wide export schema | Captures contact, location, identifier, image, status, and hours fields for later filtering. |
Where competitors win
When Apify, Octoparse, Outscraper, APIs, or scripts make more sense
Choose Apify when you want hosted actors, datasets, API calls, scheduling, webhooks, and developer-friendly run history. It fits collection that feeds software systems instead of one-off spreadsheets.
Choose Octoparse when no-code operators want visual task setup, cloud execution, and template-style workflows. Apify vs Octoparse Google Maps is mostly a choice between a developer actor platform and a hosted no-code environment.
Choose Outscraper when you want a managed scraper product with no-code and API paths. Choose PhantomBuster when the workflow is close to sales automation from a spreadsheet or Google Maps search URL.
Choose SerpApi, Bright Data, or DataForSEO when developers need API responses, localization controls, retries, and monitoring. Choose a google maps scraper GitHub project or custom script only when engineers will own parsing, browser behavior, proxy policy, tests, and breakage.
Policy and API fit
Places API vs scraper: choose the route by use case
The Google Maps Places API is the better starting point when you need an approved integration, predictable JSON, field masks, and billing controls.
A scraper is more practical when the deliverable is internal research from browser-visible pages. Even then, review the current Google Maps Platform terms, avoid bypassing access controls, collect only fields you need, keep batches modest, and document source URLs and run dates.
Decision guide
Which Google Maps scraper should you pick?
UScraper wins when you have approved place URLs from keyword research and need an inspectable local desktop app workflow. Start with Google Maps Leads Scraper by Keywords.
Google Places API wins when the work belongs in production software, needs documented API fields, or requires clearer platform governance.
Apify, Outscraper, Octoparse, and PhantomBuster win when scheduling, remote execution, cloud storage, integrations, and vendor-managed infrastructure matter most.
Scripts can win when engineers own the stack. UScraper wins when business users need editable visual logic without maintaining code.
For the template workflow, open the Google Maps Leads Scraper by Keywords page. For adjacent extractors, browse the UScraper template library or the UScraper blog.
FAQ
Google Maps scraper alternatives FAQ
Use the Places API for approved app workflows, cloud actors or scraper APIs for hosted collection, scripts when engineers own the parser, and UScraper when analysts need a visual local desktop app workflow that exports leads to CSV.