DiDi Food - Full Restaurant Database

Unlock comprehensive market intelligence with our Full Restaurant Database from DiDi Food. Gain strategic insights into all active food venues across their key operational regions, including Mexico, Brazil, Chile, and Japan.

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DATA SAMPLE

Explore Full Restaurant Database

The sample table below illustrates the breadth and depth of the granular data points we provide for the DiDi Food Full Restaurant Database. Our high-quality datasets are designed for straightforward integration into your existing analytics platforms.
Restaurant Name Cuisine Type City DiDi Rating Review Count Avg Price Level +... Additional Data Points
Sabores de México Mexican Mexico City 4.7 1289 $$ Yes - Click to unlock
Sushi Ichiro Japanese Tokyo 4.5 876 $$$ Yes - Click to unlock
Pizzaria Brasil Italian São Paulo 4.3 2154 $ Yes - Click to unlock
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The table above shows only a representative data sample.
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OTHER DATASETS

Browse Our Complete Food Delivery Data Catalog

We scrape more than just Full Restaurant Database. Find data from hundreds of platforms across the Food Delivery industry and beyond.

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Product Name & SKU, Retailer Name, Price, Discounted Price, Promotion Type (e.g., bundle, cashback), Stock Availability, Customer Ratings, Number of Sellers, and many more.

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European Hotel Pricing & Availability

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German Used Car Market Data

Car Make & Model, Year of Production, Price, Mileage (Przebieg), Engine Type (np. Diesel, Electric), Transmission Type, Location (PLZ), Seller Type (Private/Dealer), Date Listed, and many more.

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Tech & IT Job Postings in the DACH Region

Job Title, Company Name, Location (City, Country), Required Skills & Technologies, Experience Level (Junior, Senior), Salary Range (if provided), Employment Type (Full-time, Contract), Date Posted, and many more.

64.2K+
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Uber Eats Poland Dataset

Restaurant Name, Cuisine Type, Location (City, Area), Ratings, Customer Reviews, Menu Items, Prices, Discounts & Offers, Delivery Fees, and many more

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UK Real Estate Listings - Apartments

Price, Price per Square Meter, Location (City, District), Area (in m²), Number of Rooms, Floor, Building Type, Year Built, Offer Type (Sale/Rent), Market Type (Primary/Secondary), and many more.

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