Restaurants Dataset
The Restaurants dataset provides comprehensive insights into dining establishments worldwide. The dataset includes key details such as restaurant names, addresses, contact information, cuisine types, operating hours, ratings, reviews, price ranges, menus, amenities, photos, and location data, offering valuable information for market analysis, competitive intelligence, and business development.
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Available Restaurant Datasets
- Demo data in JSON/CSV
- Fresh records
- Customize, enrich, and format the data
Google Maps full information
9K+
1.1K+Google maps reviews
Yelp businesses overview
Yelp businesses reviews
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Restaurants dataset sample
The Restaurants dataset includes key details such as restaurant names, addresses, phone numbers, websites, cuisine types, operating hours, ratings, review counts, price ranges, delivery options, reservation availability, amenities, photos, geographic coordinates, and more.
Need real-time restaurant data?
Explore our Web Scraper APIs
Datasets Pricing
- Clean and validated
- Refreshed monthly
- JSON/CSV/Parquet
Power AI Agents Instantly
Our Restaurants datasets are AI/LLM-optimized: clearly structured, well-documented, with code and recipes for easy LLM/chatbot integration.
Structured & Clean
Pre-processed data with consistent schemas, perfect for AI model training and inference.
Code Examples
Ready-to-use Python, Node.js, cURL, PHP, Go, Java, and Ruby snippets for easy integration with AI workflows.
Documentation
curl --request GET
--url https://api.brightdata.com/datasets/snapshots/{id}/download
--header 'Authorization: Bearer '
import requests
url = "https://api.brightdata.com/datasets/snapshots/{id}/download"
headers = {"Authorization": "Bearer "}
response = requests.get(url, headers=headers)
print(response.json())
const url = 'https://api.brightdata.com/datasets/snapshots/{id}/download';
const options = {method: 'GET', headers: {Authorization: 'Bearer '}, body: undefined};
try {
const response = await fetch(url, options);
const data = await response.json();
console.log(data);
} catch (error) {
console.error(error);
}
HttpResponse response = Unirest.get("https://api.brightdata.com/datasets/snapshots/{id}/download")
.header("Authorization", "Bearer ")
.asString();
require 'uri'
require 'net/http'
url = URI("https://api.brightdata.com/datasets/snapshots/{id}/download")
http = Net::HTTP.new(url.host, url.port)
http.use_ssl = true
request = Net::HTTP::Get.new(url)
request["Authorization"] = 'Bearer '
response = http.request(request)
puts response.read_body
Restaurants datasets tailored to your needs
Data subscription
Subscribe to access datasets at a significantly reduced cost.
File output formats
JSON, NDJSON, JSON Lines, CSV, Parquet. Optional .gz compression.
Flexible delivery
Snowflake, Amazon S3 bucket, Google Cloud, Azure, and SFTP.
Scalable data
Scale without worrying about infra, proxy servers, or blocks.
Cost savings
Customize any dataset using filters and formatting options.
Code maintenance
Datasets are maintained based on website structure changes.
Simplified integrations
Benefit from integrations with Snowflake and AWS.
24/7 support
A dedicated team of data professionals is here to help.
Leaders in compliance
Data is ethically obtained and compliant with all privacy laws.
Get structured and reliable restaurant data
We’ll provide the data while you focus on the rest
High-volume web data
With our unblocking capabilities and round-the-clock IP rotation we ensure access to all data points on a website.
Data for immediate use
Every aspect of the data collection process is thoroughly validated as part of our robust data validation process.
Automated data flow
Create custom schedules to automate data delivery and watch the data flow seamlessly into your storage.
How companies use Restaurants datasets
Competitive intelligence
Business development
Sentiment analysis
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Restaurants Dataset FAQs
What data is included in the Restaurants dataset?
The Restaurants dataset includes different data points that fit your needs. Some of the data points include: restaurant name, address, phone number, website, email, cuisine type, operating hours, ratings, review count, price range, menu information, delivery options, reservation availability, amenities, photos, geographic coordinates, and more.
Can I get updates for my purchased Restaurants dataset?
Yes, you can get updates to your Restaurants dataset on a daily, weekly, monthly, or custom basis to track new openings and changes.
Can I purchase a subset of the Restaurants dataset?
Yes, you can purchase a Restaurants subset that will include only the data points you need. By purchasing a subset, cost is reduced substantially.
In what format will I receive the Restaurants dataset?
Dataset formats are JSON, NDJSON, JSON Lines, CSV, or Parquet. Optionally, files can be compressed to .gz.
Can I scrape restaurant data by myself?
If you don't want to purchase a dataset, you can start scraping restaurant data using our Web Scraper APIs for various platforms.
Can I get a data sample?
Yes, you can request sample data to evaluate the quality and relevance of the information provided. This is a great way to ensure it meets your needs before committing to a full dataset.
Can I request specific data points from the Restaurants dataset?
Yes, you can request specific data points from the Restaurants dataset tailored to your unique needs, ensuring you receive precisely the information you require for your projects.
Is it possible to integrate the Restaurants dataset directly into my existing systems?
Absolutely, the Restaurants dataset offers seamless API integration, allowing you to effortlessly integrate the data into your CRM, analytics tools, or any other systems you use, streamlining your operations.
Restaurants Dataset FAQs
How often is the Restaurants dataset updated?
The Restaurants dataset is available with flexible refresh schedules: one-time, bi-annual, quarterly, monthly, weekly, or daily - with deeper discounts for higher-frequency subscriptions (up to 80% off on monthly plans). You can also choose between pre-collected data (instantly available, collected within the last days to months) or freshly collected data gathered on-demand at the time of your order. The freshness window can be defined before checkout.
Can I purchase a subset of the Restaurants dataset?
Yes. You can filter the Restaurants dataset to include only the records and data fields you need - by geography, timeframe, category, or any supported field - using Bright Data's AI-powered filter tool or the Filter Dataset API. You only pay for the records in your filtered snapshot, which can substantially reduce cost. Filters support operators like equals, includes, greater than, is null, and more, with up to 3 levels of nested logic.
What formats and delivery options are available for the Restaurants dataset?
The Restaurants dataset is delivered in your choice of JSON, NDJSON, JSON Lines, CSV, XLSX, or Parquet, with optional .gz compression. Delivery destinations include: Amazon S3, Google Cloud Storage, Microsoft Azure Blob, Snowflake, Google PubSub, SFTP, Webhook, or Email. You can also download directly via the Control Panel (up to 5 GB) or retrieve programmatically via the Snapshot Download API. For snapshots larger than 5 GB, download links are sent by email.
Can I get a free sample of the Restaurants dataset before purchasing?
Yes. Every dataset in the Bright Data Marketplace - including the Restaurants dataset - offers a downloadable data sample at no cost. You can preview the data schema, field definitions, and a representative set of records to evaluate quality, coverage, and relevance before committing to a purchase. Samples are available directly from the dataset page in the Bright Data Marketplace.
Can I request specific data fields or a custom version of the Restaurants dataset?
Yes. You can customize the Restaurants dataset to include only the specific fields you need, hiding irrelevant columns to reduce cost and simplify integration. For more advanced needs - such as a proprietary data schema, enriched fields, or a source not currently in the marketplace - Bright Data's team can build a custom dataset tailored to your requirements. Contact the sales team to discuss your use case.
How does the Restaurants dataset integrate with my existing systems and workflows?
The Restaurants dataset is built for seamless integration. You can pull data programmatically using the Marketplace Dataset API (with SDKs available for Python and JavaScript), push results directly to your data warehouse or cloud storage, or connect via native integrations with tools like Snowflake, AWS, Google Cloud, Databricks, and automation platforms like Zapier, Make.com, and n8n. The async workflow (trigger - poll - download) makes it easy to embed into any pipeline.
Is the Restaurants dataset ethically sourced and legally compliant?
Yes. All Bright Data datasets - including Restaurants - are collected exclusively from publicly available online sources in compliance with applicable laws and regulations, including GDPR, CCPA, and Bright Data's own Code of Ethics. Bright Data holds ISO 27001 certification and is SOC 2 compliant. Data undergoes rigorous quality assurance before delivery. You can review Bright Data's full compliance posture at the Trust Center.
What does the Restaurants dataset cost, and are there volume discounts?
Pricing for the Restaurants dataset starts at $250 for 100K records (approximately $0.0025 per record) for a one-time purchase. Subscription plans unlock significant savings: up to 25% off bi-annual, 50% off quarterly, and 80% off monthly refresh plans. Volume tiers are available for 100K, 500K, 1M, 5M, and 20M+ records. Dataset bundles (purchasing two or more datasets together) and smart update options (paying only for new or changed records) provide additional savings. For enterprise-scale pricing, contact the Bright Data sales team.
What is a snapshot, and how does the Restaurants dataset delivery process work?
When you order the Restaurants dataset - or filter it via API - Bright Data generates a snapshot: a point-in-time export of your selected records. The async workflow runs as follows: (1) your order or API call triggers the collection job; (2) you can poll the job status using the snapshot ID; (3) once complete, you download the snapshot via the API or your configured delivery destination. Snapshot metadata (including error codes and initiation type) is accessible via the Snapshot Metadata API.
Can I use the Restaurants dataset for AI and machine learning projects?
Yes. The Restaurants dataset is structured and validated for immediate use in AI and ML workflows, including LLM fine-tuning, model training, RAG pipelines, and agent knowledge bases. Data is delivered in standard ML-ready formats (JSON, Parquet, NDJSON) with consistent schemas and documented field definitions accessible via the Dataset Metadata API. Bright Data also offers specialized AI data packages and a web archive with 50+ PB of historical data for large-scale pre-training.