Apify Google Maps Scraper: Honest Review (2026)

Apify is the developer-friendly scraper marketplace, and its Google Maps actors are some of the most popular tools in the entire catalog. If you have spent any time researching how to pull business data out of Maps at scale, you have probably landed on the Apify store more than once. This is an honest review of the Apify Google Maps Scraper in 2026 — what genuinely works, where it falls short, what it really costs once you account for everything, and who should pick something else. We have run the actor, parsed the datasets, and compared the workflow against purpose-built alternatives. The goal is not to bash a respected platform; it is to help you decide whether the Apify Google Maps Scraper is the right tool for your specific job, or whether a leaner option will save you time and money.

What the Apify Google Maps Scraper actor is

Apify is a cloud platform that hosts thousands of scrapers, called actors. Each actor is a containerized program that runs on Apify's infrastructure, takes a JSON input, and produces a dataset you can download or pull through an API. For Google Maps specifically, you will find two flavors of actors. The first is the official Apify Google Maps Scraper maintained by the Apify team. The second is a long tail of community actors built by independent developers, each with its own quirks, update cadence, and pricing model.

The official actor accepts inputs like search terms, location filters, latitude and longitude bounds, language, and the maximum number of places to scrape per query. It returns rich JSON records: business name, address, phone, website, category, opening hours, average rating, review count, place ID, coordinates, and often a list of reviews and images. You can run it through the Apify Console, schedule it on a cron, or trigger it from your own backend through the Apify API. Output lives in a dataset that you can download as JSON, CSV, Excel, or push to integrations like Google Drive, Zapier, or webhooks.

The mental model matters here. Apify is not a finished sales tool. It is a programmable scraping runtime. You bring the use case, you wire the inputs, you process the output. That is its core strength and its core friction.

Pricing

Apify pricing is usage-based, and that is where most newcomers get tripped up. You pay for compute units, which are a function of how much memory the actor consumes and how long it runs. You also pay for proxy traffic when the actor uses Apify's residential or datacenter proxies, for dataset storage if you keep results around, and for actor-specific rental fees on some marketplace listings. Apify offers a free tier with monthly platform credits, then paid plans that bundle a larger credit allowance with team features and higher concurrency.

The honest part of the review: the unit economics depend heavily on what you are scraping. A small run on a tight geographic area with a narrow query is cheap. Scraping every restaurant across a metro area with reviews and photos pulled in can burn through credits faster than the dashboard suggests, especially when retries kick in or when Maps changes its layout and runs take longer. You can absolutely budget Apify costs once you have a few runs under your belt, but the first month is typically a learning tax. Compare that with a flat-credit model and the cost predictability gap is real.

We are not quoting specific Apify dollar figures here because they shift, and per-actor rentals vary across the marketplace. Check the Apify pricing page and the actor detail page before any serious run.

Strengths

The Apify Google Maps Scraper has genuine strengths that explain its popularity.

Developer ergonomics are excellent. The Console is clean, the API is well documented, the SDKs in JavaScript and Python are mature, and the actor input schemas are introspectable. If you write code for a living, you will be productive on Apify in an afternoon.

The marketplace is a real moat. If the official Maps actor does not do exactly what you need, there is almost certainly a community actor that does, or one close enough to fork. You also get adjacent actors for reviews, photos, and contact enrichment that you can chain together.

Scheduling is built in. Cron, conditional runs, and webhook triggers make it straightforward to keep a dataset fresh without standing up your own infrastructure.

Proxies are included. You do not have to bring your own proxy provider for most jobs. The actor handles rotation, retries, and basic anti-bot handling, which is non-trivial work if you were to build it from scratch.

The dataset API is a quiet superpower. Every run writes to a dataset you can query, paginate, and stream into a warehouse. For teams that want to own their data pipeline, this is exactly the right primitive.

Weaknesses

The weaknesses are the mirror image of the strengths.

There is a technical bar. To get real value out of Apify, you need to be comfortable with JSON, API tokens, basic scripting, and at least some idea of what proxies and rate limits are. Non-technical operators stall here.

The output requires post-processing. Raw Maps data is messy. You will get duplicates across overlapping queries, partial records where Google withheld a field, phone numbers in inconsistent formats, websites that are actually Facebook pages, and categories that need normalization. Apify gives you the firehose. Cleaning it is your job.

Cost unpredictability is the most common complaint we hear. Compute units, memory tier, storage, and proxy traffic all combine into a bill that is not easy to forecast on day one. Teams used to flat per-lead pricing find this uncomfortable.

There is no CRM-style UI. You cannot tag a lead, drop it into a list, mark it as contacted, or share a workspace with a teammate the way you would in a sales tool. Apify is not trying to be that, and that is fine, but it means you need a second tool downstream.

There is no built-in deduplication across runs. If you scrape "dentist Lyon" today and "orthodontist Lyon" next week, you will get overlap, and merging those datasets is on you.

Apify vs MapsLeads — head-to-head

| Dimension | Apify Google Maps Scraper | MapsLeads | |---|---|---| | Primary user | Developers, ops engineers | Sales teams, agencies, founders | | Setup time | Hours to days | Minutes | | Pricing model | Compute units, memory, storage, proxy | Flat credits per lead and module | | Output | Raw JSON dataset | Clean rows with modules per lead | | Deduplication | Manual, post-processing | Built-in across groups | | Contact enrichment | Chain another actor | Contact Pro module, one click | | Reputation signals | Manual parsing | Reputation module, one click | | Workspace, groups, tags | Not included | Built-in groups | | Export | JSON, CSV, Excel, integrations | CSV, Excel, Google Sheets | | Best for | Custom pipelines, large engineering teams | Day-to-day prospecting and outreach |

For a deeper feature-by-feature breakdown, see MapsLeads vs Apify Google Maps. If you want to widen the field, the best Google Maps scraper tools compared post puts both in context against the rest of the market, and our Google Maps scraper API guide covers the programmatic side specifically.

Who Apify is for

Apify is the right choice when you have engineering capacity and a use case that does not fit a finished product. If you are building an internal tool, enriching a data warehouse, running market research at scale across many countries, or composing several scrapers into a custom pipeline, Apify gives you the primitives and gets out of the way. Ops engineers love it. Data teams love it. Anyone who wants the dataset and not the workflow will be happy on Apify.

It is also a good fit if your scraping needs go far beyond Google Maps. The same account, the same billing, and the same SDK cover hundreds of other sources, which is a real advantage if you are consolidating tools.

Who MapsLeads is for

MapsLeads is built for the people who do not want to write code and do not want to think about compute units. Sales teams running outbound. Agencies prospecting on behalf of clients. Founders building a first list of targets in a new vertical. Local SEO consultants pulling reputation signals before a pitch. The job is not "scrape the web." The job is "give me a clean list of qualified businesses with phones, emails, and reputation scores so I can start calling on Monday."

If that sounds like your job, you do not need a programmable runtime. You need a search bar, a few toggles, and an export button.

How MapsLeads handles the same use case

Here is the workflow end to end. Open MapsLeads and run a Search by typing your query and your city — for example, "dentist" in "Lyon." The base result returns one credit per lead with name, address, phone where Google exposes it, website, category, rating, and review count. From there you decide which modules to enable.

Turn on Contact Pro for plus one credit per lead. The module finds verified email addresses associated with the business beyond what Google shows, plus social profiles where available, so your outreach has a real inbox to land in rather than a generic contact form. Turn on Reputation for plus one credit per lead. You get a structured view of recent reviews, average sentiment, and reputation flags that tell you whether a business is happy with its current situation or actively looking for help. If you also need visual context, the Photos module pulls business photos for plus two credits per lead.

Results land in groups. Groups are workspaces tied to a query and a city, and they are where dedup happens automatically. If you run "dentist Lyon" and later "orthodontist Lyon," MapsLeads detects the overlap by place identity and keeps a single clean row per business, so you never pay twice and you never email the same dentist twice. When the group looks right, export to CSV, Excel, or Google Sheets and push it into your CRM or sequencing tool.

Credits live in your wallet. Billing is flat: one credit Base, plus one for Contact Pro, plus one for Reputation, plus two for Photos. No compute units, no memory tiers, no surprises. See Pricing for current credit packs.

FAQ

Is Apify good for Google Maps scraping? Yes, if you are a developer and you want a programmable scraping runtime. The official actor is solid, the marketplace covers edge cases, and the API is clean. If you are a sales operator, it is overkill.

How does Apify pricing work? Apify charges based on compute units, memory tier, dataset storage, and proxy usage, layered on top of a monthly platform plan. Some marketplace actors add a rental fee. The model is flexible but harder to forecast than a flat per-lead price. Always check the live pricing pages before a large run.

What is a good Apify alternative for sales teams? MapsLeads is the most direct alternative if your goal is prospecting rather than building a data pipeline. You get Search, Contact Pro, Reputation, Photos, groups, dedup, and export without writing any code. For broader options, the best Google Maps scraper tools compared post is a good starting point.

MapsLeads vs Apify — which should I pick? Pick Apify if you have engineers and you want raw data flowing into your own systems. Pick MapsLeads if you want clean leads with contact and reputation signals, ready to export and call. The full breakdown is in MapsLeads vs Apify Google Maps.

Can I get a Google Maps scraper API instead of a UI? Yes. Apify exposes its actors through an API, and MapsLeads has its own API surface as well. Our Google Maps scraper API guide covers the tradeoffs.

Does Apify deduplicate results across runs? Not by default. You handle dedup in post-processing. MapsLeads deduplicates inside groups automatically.

Verdict

The Apify Google Maps Scraper is a good product for the audience it is built for. If you are an engineer who wants a programmable runtime, schedule it, take the dataset, and own the rest of the pipeline. If you are a sales team or an agency, the same job is faster, cheaper, and less stressful inside a tool that already understands what a lead is.

Try MapsLeads free and pull your first clean list in minutes. Get started.