Bright Data vs Scrap.io: Complete Google Maps Scraper Comparison for Lead Generation

Table of Contents

• Starting with Bright Data: The World's Number One Web Data Platform
• Method 1: Web Data Sets - Buying Pre-Existing Data
• Method 2: The AI Tool - Promise vs Reality
• Method 3: Web Scrapers - Where Things Get Serious
• The Scrap.io Difference: Real Scale, Real Results
• The API Route: More Complexity, Same Limitations
• Method 4: The Proxy Network and Its Complications
• The Final Verdict
• Frequently Asked Questions

In this video, we are going to take a look at the differences between Bright Data and Scrap.io in terms of lead generation. Let's check it out. Let's start with Bright Data. According to the description, Bright Data is the world's number one web data platform. I have a confession to make. I worked with them once or twice about four years ago. So the way I would describe it in my own words is Bright Data delivers the infrastructure to collect data at scale without getting blocked.

When logging into the interface for the first time, you have access to four different ways to do so.

Method 1: Web Data Sets - Buying Pre-Existing Data

The first one is called web data sets. This is useful if you want to buy already existing data. Scrap.io is also a web data set, but laser focused on Google Maps. So to make a fair comparison, let's type Google Maps into the search bar. Here we go. Google Maps full information. We have a total of 75 million leads. And if we click on statistics, we notice the records are updated at least once a month.

Now, I like you guys, but I wasn't ready to spend $250 for a 10-minute tutorial. Fortunately, we can freely download the sample in CSV or JSON format. To make it more interesting, I've also downloaded another file, this time from Scrap.io. I put both files side by side to compare.

They both have data such as:

• Place ID
• Name
• Address
• Category
• Review count
• Rating
• Website
• Phone number
• Is claimed
• And other minor details

So far, we have collected comprehensive Google Maps data, but no enriched data.

On second thought, Scrap.io can allow you to directly enrich data based on the website. We might have a chance to retrieve:

• Email addresses
• Social media links
• Contact pages
• Metadata
• And in overall over 70 different columns

We will leave you a sample in the description if you want to check it out.

Method 2: The AI Tool - Promise vs Reality

Off the bat, I want to say that if anyone's AI tool promises to scrape any site for you, then most likely lying. The speaker here is named John Watson Rooney. He's probably in the S tier of YouTube creators dedicated to learning Python, web scraping, and APIs. So when one of the key figures of web scraping is pointing out AI as being detrimental to the industry, let's say it draws attention.

One may safely wonder whether the new AI tool from Bright Data will truly allow you to transform plain English queries into structured data sets or is it another shiny fashionable feature? Let's check that out.

Now, if you are new to this, I would still recommend you to take a look at the documentation. So, you can learn what a good prompt looks like. For example, we can write:

"Find all fintech companies in Brazil that raised funding in the past 18 months and offer earned wage access. Show company name, HQ city, last funding round, CEO name."

It leads us to the following formula: Find all entities that meet conditions. Show: column 1, column 2, column 3, blah blah blah.

I've seen in the Scrap.io file that we can gather the column website meta generator as enriched data so we can know which sites have the mention Wix.com website builder for example. Can we do a similar thing on Bright Data? I thought it was going to be easy. Unfortunately, something unexpected happened.

Look at this. I cannot use the AI lookup feature because I'm logged in with a personal email address and it's for business emails only. Now, this is not the end of the world. I'm going to create another account and I see you back in a moment.

So, here is what I've written: "Find all restaurants in Charlotte, North Carolina, USA on Google Maps that have Wix.com website builder as the website meta generator value. Show name, address, website meta generator."

Let's take a look together. So, we have access to a preview, but much more interesting, the AI is suggesting us some refinements. So, I've asked for restaurants as a main activity only, only opened restaurants and within the city limits only. And based on this criteria, we can come back to our database.

We have 75 records as expected. However, it seems that the database hasn't been filtered in the sense that we have a mix of websites containing a Wix's metadata and those not containing a Wix's metadata. But anyway, let's take a closer look by downloading a sample.

And at least we have a column with the reasoning, meaning the reason why the Wix website check is set up to yes or no. "The evidence strongly supports that the site does not use Wix. Therefore, it has been set up to no." "The website explicitly shows Wix's branding in the snippet and page content. Therefore, it has been set up to yes."

Oh, and for the record, directly after saying "off the bat that I want to say that if anyone's AI tool promises to scrape any site for you, then most likely lying," John Watson Rooney qualified his opinion. "Don't get me wrong, AI does have a place in our workflow, but the world of scraping consistently at scale has much bigger issues that it can't really solve."

Regarding the scalability issue, here is how it has been addressed in Bright Data's documentation. The maximum absolute limit per query is a thousand records. One may assume that they are perfectly aware of what they are doing. AI is a cool trick. However, it's not magical and most importantly not scalable.

Method 3: Web Scrapers - Where Things Get Serious (Or Do They?)

The third one is web scrapers. This is where things get serious. Choose your target domain, set your parameters, and start collecting data. What are we waiting for? Google.com.

We end up with four scrapers related to Google Maps:

• Discover by CID
• Discover by place ID
• Collect by URL
• Discover by location

I'm going to go for discover by location as we want batches of new leads rather than having them enriched one by one. If you click on it, two options are displayed: Scraper API and No-code scraper.

I tried them both and because I'm not a web developer and by that I mean this is like Elvish to me. So let's start with the no-code scraper option.

As an input we face five criteria:

• Country
• Latitude
• Longitude
• Zoom level
• Keywords

But only these two are required. As an example, I'm looking for restaurants in Charlotte, North Carolina, USA. In the, well, United States.

I can click and select a custom output schema. This means picking up only some output fields while removing other unnecessary ones. Let's click and start collecting. After a few moments, it is done. You have your files within the logs tab with the status, the success rate, and the number of records.

Okay, let's download it in CSV format. And this is what it should look like. Well, this method works superbly well with the same columns as the one from the web data sets, but - and this is what makes me want to bang my head against the wall - the scraper has a limitation of 200 businesses per location.

The Scrap.io Difference: Real Scale, Real Results

And by making the very same request on Scrap.io, I can tell you there are way more than 200 results. Look at this. This is what the interface looks like on Scrap.io. We were looking for restaurants. If my memory serves, it was in the US and more specifically North Carolina, right? Targeting a city called Charlotte.

I click on search. And how many leads do we expect to get? Around 2,000 results. So this is only an estimate because if I click on export, Scrap.io is going to re-extract the data to make sure we have access to real-time data.

I can also filter my database. Let's say close permanently: No, with a website. I click on filter and then I can click on exports. And all the exports I have done so far can be found within the my exports tab. And for each and every one of them, I can download in CSV or Excel format.

Let's come back to Bright Data. Maybe the scalability problem can be overcome by the second option, the scraper API. Let's jump into it, shall we?

The API Route: More Complexity, Same Limitations

To the right of the screen, we have access to the code example. Let's make it Python friendly. It seems we might also need an API key. We can achieve this by going to account settings and clicking add key.

I really appreciate the idea that we can set up an expiration date, which allows me to edit this video without the need to blur the key at every single frame. Thank you. I've also limited the records to 30 to test the code faster.

Finally, I copied, paste the code, and ran it once. And by doing so, I end up with a snapshot ID, but also another entry within my logs tab. When the status is switched to ready, I can manually download my file. Also, more conveniently, I can monitor the progress of my scraping.

The documentation can be found by visiting this URL. I can try it. And as long as I get my bearer token and my snapshot ID, it should work just fine. The final status can range from ready and running to failed.

By the way, something I haven't mentioned because it's not its main purpose, but Bright Data doesn't have a monopoly on APIs. Scrap.io can also do a bunch of cool stuff. If you click on API at the bottom of the landing page, here is what you are going to see. A list of our API endpoints, but my favorite is without a doubt, the Enrich API.

With that one, I can look up Google Maps information related to a domain name, an email address, or a phone number. What I usually do is to take my list of websites. Then I'm using this API as an indirect way to easily scrape websites. I know I'm making my life difficult. I like coding, but coding doesn't like me.

Method 4: The Proxy Network and Its Complications

We cannot talk about Bright Data without mentioning its proxy network. Among the list, we are going to focus on residential proxies as they are more reliable in the long run. Just a word about how to set them up.

Okay, I click on get started. I type a zone name. I can specify default countries, US, Poland, and France. All that remains to do is to choose a proxy type, shared pool or dedicated. Having access to dedicated proxies sounds like a better plan. So, let's click on dedicated.

Wait, wait, wait, wait, wait. What do you mean I cannot unlock it?

Can you talk a bit about that? About what you have put in place to make sure that you can use this residential proxy.

"Yeah, sure."

The man who is talking here is Ronny Shalit. He is the chief compliance analytics officer at Bright Data. This can be translated as:

"My job is to make sure you are not using our proxies to harm someone else's website."

"This is a challenging part because when you set up a platform, any SaaS platform for that example, you want to have as less friction as possible but with Bright Data we do have that in place but as you need more and more special access rights and residential system, the residential network is one of them. We need to get to know you better and this is why we took the KYC, the know your customer process which basically we ask two different questions: the first one is who you are and the other part is to know what exactly is your use case. The result at the end of us being, you know, we don't approve or don't accept hundreds if not thousands of customers on a yearly basis."

Now Bright Data's verification process is divided into eight different steps. It might look overwhelming and it sure does create friction as the approval process can take up to one to two business days.

To be honest, while making this video, I hesitated to show you how I go through the whole process. But my ethics dictate not to bother a poor sales manager for something I will barely use. Let's keep it to shared and add the new zone.

Finally, I can test it in the playground tab. I run my request and I'm located in the US. I run it one more time and now I live in Poland. A couple more tries later and I'm finishing my race eating frog legs in France. Your proxy is good to go.

The Final Verdict

To summarize, here are your four ways to gather leads with Bright Data:

1. Web data sets
2. AI lookup
3. Web scrapers
4. Proxies

However, as we have seen with the exception of web data sets, all other options require additional effort and often solid coding knowledge alongside. Even if we consider the biggest lead database on the planet, we can unlock nearly 75 million leads at our fingertips. That number even scares me.

Or maybe it doesn't. Of course, such a list cannot be exhaustive, but can't we get more? What do you think? How many businesses are listed globally on Google Maps?

Google indexes 200 million+ businesses worldwide.

For scraping Google Maps, Scrap.io is a no-brainer solution. On Scrap.io, we don't provide the infrastructure for you to code your scraper. We simply provide you real-time direct quality data within a couple of clicks. And with the proper plan, I can collect leads at the scale of a country without even needing to think about it. I'm sorry to brag a little.

The Bottom Line Comparison

When you compare these two platforms side by side, the differences become crystal clear. Bright Data offers infrastructure and tools that require technical expertise, coding knowledge, and patience with approval processes. Their AI tool is limited to 1,000 records, their no-code scraper caps at 200 businesses per location, and accessing their full features requires jumping through compliance hoops.

Meanwhile, Scrap.io delivers 10x more results for the same search (2,000 vs 200 for restaurants in Charlotte), provides over 70 columns of enriched data automatically including emails and social media profiles, offers real-time extraction without outdated databases, and requires zero coding knowledge - just a few clicks and you're done.

With 200 million businesses indexed and the ability to extract an entire country's data in just two clicks, Scrap.io stands out as the most powerful no-code Google Maps scraper available. The platform was designed from the ground up to make Google Maps data extraction accessible to everyone, not just developers.

The choice really depends on your needs. If you're a developer who wants to build custom scraping infrastructure and doesn't mind complexity, Bright Data might work for you. But if you want actual leads, enriched data, and results at scale without the technical headache, Scrap.io is the clear winner for business lead generation and real-time data extraction.

Frequently Asked Questions

Why does Google Maps only show 120-200 results when scraping?

Google Maps implements these limitations to prevent excessive automated data extraction. Most traditional scrapers hit a wall at 120 results due to Google's infinite scroll limitations, while some API-based solutions like Bright Data's no-code scraper cap at 200. However, advanced solutions like Scrap.io can bypass these limitations by using proprietary technology to access the full dataset, delivering 2,000+ results for the same search query. This is a fundamental limitation that even expensive tools struggle with - except Scrap.io.

Do I need coding skills to scrape Google Maps data?

Bright Data and Scrap.io differ in technical requirements. Bright Data requires coding knowledge for full features (API integration, Python scripts), with their no-code option limited to 200 results. Scrap.io is 100% no-code from start to finish, allowing anyone to extract 2,000+ results with enriched data through a simple point-and-click interface.

The detailed difference: While Bright Data offers both API solutions (requiring coding) and a no-code scraper, the no-code option is severely limited. As I discovered in my testing, even their no-code option required understanding technical concepts like latitude, longitude, and zoom levels. Scrap.io is designed for non-technical users from the ground up.

What's the difference between using Google's official API and web scrapers?

Google's official Places API has strict limitations: expensive pricing (around $17 per 1,000 requests for basic data), limited data points (no emails or social media), strict rate limits (you can hit quota limits quickly), and daily quotas that can stop your data collection mid-process. Web scrapers like Scrap.io can extract much more comprehensive data including emails, social media links, and 70+ data points that aren't available through the official API. Plus, there are no rate limits or daily quotas to worry about - you can extract as much as you need, when you need it.

How much does Google Maps data extraction typically cost?

Pricing varies significantly and can be confusing. Bright Data's web datasets start at $250 just for samples, with their Scraper APIs beginning at $500/month - and that's before you even consider proxy costs. In contrast, Scrap.io offers transparent, straightforward pricing starting at just €49/month for 10,000 export credits, with a generous 7-day free trial including 100 export credits so you can test it properly. The cost per lead with Scrap.io typically works out to less than €0.005 per contact - a fraction of what you'd pay elsewhere.

Is Google Maps scraping legal?

Yes, extracting publicly available data from Google Maps is legal in both the US and EU. This has been confirmed by multiple court cases. Both Bright Data and Scrap.io comply with data protection regulations like GDPR. The key is that they only extract publicly available information that businesses have chosen to display on their Google Maps listings. Scrap.io explicitly states they are GDPR compliant and only collect public data authorized by law. You're essentially automating what you could do manually - visiting each listing and copying the information.

How can I extract emails and social media profiles from Google Maps?

This is where Scrap.io truly excels and Bright Data falls short completely. While Bright Data's Google Maps scraper doesn't offer email or social media extraction capabilities at all (I checked - even their most expensive plans don't include this), Scrap.io automatically enriches each listing with emails, Facebook, Instagram, YouTube, Twitter/X, and LinkedIn profiles when available. The platform actually visits the business websites listed on Google Maps and intelligently extracts this additional contact information. This single feature alone can save hours of manual work per lead.

What's the fastest way to extract data at country scale?

Scrap.io is the only solution that allows you to extract all businesses from an entire country with literally just two clicks. You simply select your country, choose your categories (or leave blank for all businesses), and click export. This feature is available on their Company plan (€499/month for 100,000 export credits) and is technically impossible to achieve with traditional scrapers due to API limitations and complexity. I tested this myself - with Bright Data, you'd need to write complex code to iterate through every city and region, and even then you'd hit the 200-result limitation repeatedly.

How do I handle IP blocking and captchas when scraping?

This is where things get really complicated with Bright Data. They address this with their proxy network, but as I discovered, it requires additional setup, KYC verification (taking 1-2 business days with eight different verification steps), choosing between shared and dedicated proxies, configuring rotation settings, and significant extra costs. Scrap.io handles all of this automatically in the background - their system simulates human behavior and manages all anti-bot measures internally. You never have to worry about proxies, captchas, or IP blocking. It just works.

Can I schedule automatic extractions?

While Bright Data requires you to set up complex scheduling through their API or third-party tools, Scrap.io integrates seamlessly with automation platforms like Make.com (formerly Integromat). They even provide free pre-built workflows and scripts that you can use immediately. This means you can set up automatic daily, weekly, or monthly extractions without any coding - perfect for keeping your lead database fresh and updated.

What about data accuracy and freshness?

This is a critical difference I discovered during testing. Bright Data's datasets are updated "at least once a month" according to their documentation, meaning you could be working with data that's 30 days old. Scrap.io extracts data in real-time directly from Google Maps and the associated websites. When you click export, it's actually visiting those pages right now and pulling the current information. For businesses where phone numbers, hours, or contact details change frequently, this real-time approach is essential.

Ready to experience the difference yourself? Try Scrap.io free for 7 days with 100 export credits. See why thousands of businesses have already made the switch from complex scraping tools to the simplicity and power of Scrap.io.