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G Maps Extractor VS mlsql

Compare G Maps Extractor VS mlsql and see what are their differences

GME
G Maps Extractor

A scraping tool for business leads, one click to extract data from Google Maps search results and export to csv file, includes phone number, email address and social media profiles.

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Rating
0 reviews
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Alternatives Is it good?
mlsql

Infer SQL queries from plain-text questions and table headers.

Rating
0 reviews
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Alternatives Is it good?
InboxAgent
InboxAgent uses AI to read your shared mailboxes, like info@ and sales@, plus everyone's own inbox, on Microsoft 365, Gmail, Zoho Mail or IMAP. It finds the sales leads and gives each an owner on a board. Never sends from your mailbox. sponsored
Note: These products don't have any matching categories. If you think this is a mistake, please edit the details of one of the products and suggest appropriate categories.

Which is more popular?

Based on our record, mlsql seems to be more popular. It has been mentioned 2 times since March 2021.

social mentions
0 vs 2
Lead Generation popularity
100% vs 0%
alternatives listed
87 vs 1

Base details

Website, pricing, platforms and company facts side by side.

GME
G Maps Extractor
mlsql
Website gmapsextractor.com github.com
Pricing
Official pricing
—
Listed in
Sales Lead Generation Maps Data Extraction Browser Extensions +2
Education LMS Online Learning Web App +1

Features and specs

What each product offers, as listed by its team.

GME
G Maps Extractor 5 features
mlsql 0 features
  • Bulk Data Extraction
    G Maps Extractor allows users to extract large volumes of business data from Google Maps efficiently, including business names, addresses, phone numbers, emails, websites, ratings, and reviews, saving significant manual research time.
  • Easy to Use
    The tool is designed with a straightforward interface that doesn't require advanced technical skills or coding knowledge, making it accessible to marketers, sales teams, and small business owners who need lead generation data.
  • Export Options
    Extracted data can be exported in common formats such as CSV and Excel, making it easy to integrate the collected information into CRMs, spreadsheets, and other business tools for further processing.
  • Time-Saving for Lead Generation
    Instead of manually searching and copying business information from Google Maps one by one, the tool automates the entire process, dramatically reducing the time needed for prospecting and lead list building.
  • Search Filtering Capabilities
    Users can search and extract data based on specific keywords, locations, and business categories, allowing for targeted data collection that matches specific business needs and geographic areas of interest.

Possible disadvantages

  • Google Terms of Service Concerns
    Scraping data from Google Maps may violate Google's Terms of Service, which could lead to potential legal issues or account restrictions. Users should be aware of the legal and ethical implications of automated data extraction.
  • Data Accuracy Issues
    Extracted data may not always be up-to-date or accurate, as Google Maps listings can contain outdated phone numbers, incorrect addresses, or incomplete business information that hasn't been verified or updated by business owners.
  • Limited Free Version
    The free tier or trial version typically has significant limitations on the number of records that can be extracted, requiring users to purchase a paid plan to access meaningful volumes of data for serious business use.
  • Potential for IP Blocking
    Excessive or aggressive scraping can trigger Google's anti-bot measures, potentially leading to IP blocks, CAPTCHA challenges, or temporary restrictions that interrupt the extraction process and reduce reliability.
  • Privacy and Compliance Risks
    Using extracted contact data for cold outreach or marketing purposes may conflict with data privacy regulations such as GDPR or CAN-SPAM, putting users at risk of non-compliance if the data is not handled properly.

No features have been listed yet.

Analysis

An editorial look at what each product does well and who it suits.

GME
G Maps Extractor
mlsql

Overall verdict

  • G Maps Extractor is a solid, cost-effective tool for extracting business data from Google Maps, offering fast bulk scraping and reliable exports for lead generation and market research.

Why this product is good

  • Extracts detailed business data such as names, addresses, phone numbers, websites, ratings, and reviews directly from Google Maps
  • Supports bulk scraping, allowing users to gather large volumes of leads quickly and efficiently
  • Offers convenient export options like CSV and Excel for easy integration into CRMs and marketing workflows
  • Typically more affordable than many competing scraping tools, making it accessible for small businesses
  • User-friendly interface that requires little to no coding knowledge to get started

Recommended for

  • Sales and lead generation teams building prospect lists
  • Digital marketing agencies conducting local business outreach
  • Small business owners researching competitors and local markets
  • Freelancers and consultants needing quick access to business contact data
  • Market researchers gathering location-based business insights

Overall verdict

  • MLSQL is a solid open-source unified platform that blends SQL with machine learning, making data engineering and ML workflows accessible through a single, declarative language. It's a good choice for teams looking to streamline big data and ML pipelines without switching between multiple tools.

Why this product is good

  • It unifies data processing and machine learning under a single SQL-like syntax, lowering the learning curve for data teams.
  • Built on top of Apache Spark, it leverages a proven distributed computing engine for handling large-scale data.
  • Open-source and actively developed, allowing customization and community-driven improvements.
  • Supports the full ML lifecycle including data preprocessing, training, and deployment within one workflow.
  • Reduces the need to context-switch between separate ETL, analytics, and ML tools.

Recommended for

  • Data engineers and data scientists who prefer SQL-centric workflows
  • Teams working with big data on Apache Spark
  • Organizations wanting to unify ETL and machine learning pipelines
  • Companies seeking an open-source alternative to fragmented ML tooling
  • Analysts looking to build ML models without deep programming expertise

Category popularity

How often each product is chosen within a category, 0–100% relative to the other.

Score bands 0–20 21–40 41–50 51–60 61–100
GME
G Maps Extractor
mlsql
100% 100%
Lead Generation
0% 0%
0% 0%
LMS
100% 100%
100% 100%
Web Scraping
0% 0%
0% 0%
Web App
100% 100%

User comments

Share your experience with using G Maps Extractor and mlsql. For example, how are they different and which one is better?

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Social recommendations and mentions

Recommendations tracked on public social media and blogs since March 2021.

GME
G Maps Extractor 0 mentions
mlsql 2 mentions

Tracking G Maps Extractor since Dec 2025.

  • Download the files from Docker Container and locally edit them
    I am working on a project that requires me to take user input (as English) and return SQL queries. We will eventually be working with multiple datasets, which is why the valuenet over at https://github.com/paulfitz/mlsql ended up being... Source: over 4 years ago
  • Clone and edit Docker Projects hosted on Github
    I found this great resource here: https://github.com/paulfitz/mlsql. Source: almost 5 years ago

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