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337,187 World Hotels Database with 3.7 Million Photo Images by City, State, Country

Database Description:

This database features 337,187 hotel records (including motels, inns, B&B, hostels, etc.) and over 3.7 million hotel images (70GB). This is the 3rd edition of The Data Planet World Hotels database. It's currently the most comprehensive world hotels / global travel accommodations database you can find on the web. It is very well structured with a total of 19 tables. The hotel table has 38 different data fields for each of the hotel records.

There are a total of 337,187 international hotels (384 global or local hotel chains) from 226 countries, 3,675 sub-national areas (states, provinces, municipalities, major cities, major airports, etc.), 27,182 sub-sub-national areas and so forth 15,288 sub-sub-sub-national areas.

Each hotel is identified with one or more of 177 different features such as 24 Hour Reception, Air Conditioned, Beach (Direct Access / Nearby), Bicycle Rental, Casino, Golf Courses, Gym, Lake, Parking, Swimming Pool, etc., which are further categorized into 5 types.

There are a total of 3,723,510 JPEG image files of the rooms, facilities and views of the hotels.

In the hotel table, some of the most useful data fields include: hotel name, address, email, website, phone, fax, longitude, latitude, star rating, number of rooms, price in USD, check in / check out hours, a brief description, some FAQs, summarized customer reviews and ratings in various aspects.

There are also 18,560 + 21,359 places of interest / sightseeing attractions / trip-worthy locations across the world with precise latitude and longitude so you can calculate the distance from any of the hotels to those tourist attractions.

Hotel property types: Hotel, Motel, Inn, Bed & Breakfast, Vacation Rental, Hostel, Retreat, Resort, Other, Apartment.

Location types: Airport, Attraction, Beach, Business Area, Convention Centre, District, Institution, Landmark or Monument, Marina, Museum, Park, Popular Area, Shopping Area, Stadium or Arena, Theatre, Train Station.

Database Meta:

  • Size: 1572.34 + 71489.1 MB
  • Images / Multi-media: 3,723,510 JPEG image files, 69.8 GB. File name by database field: hotel_image.path
  • Last updated: Apr. 25th, 2014
  • Formats Included: MySQL 5 SQL dump text file, CSV, MS Excel
  • Tables: 19

Buy Now & Download: $589.95 (USD)


phpMyAdmin Screenshots:

MySQL Database: 337,187 World Hotels Database with 3.7 Million Photo Images by City, State, Country for Sale

Table Details (Data Structure / Schema):

  • chain
    Records:384

    All the hotel chains, associated with hotels by id.

    Data fields

    1. id: int(11)
    2. title: varchar(255)
    3. slug: varchar(255)
  • country
    Records:226

    Table of countries, regions and territories across the world, with ISO country codes and dial codes.

    Data fields

    1. id: int(11)
    2. title: varchar(255)
    3. slug: varchar(255)
    4. iso_country_code_2: char(2)
    5. iso_country_code_3: char(3)
    6. calling_code: varchar(255)
    7. count: int(11)
  • country_sub
    Records:3,675

    Sub-national entities such as states, provinces, major cities, etc.

    Data fields

    1. id: int(11)
    2. title: varchar(255)
    3. slug: varchar(255)
    4. type: varchar(255)
    5. country_id: int(11)
    6. count: int(11)
  • country_sub_sub
    Records:27,182

    Sub-sub-national entities such as towns, villages, tourist regions, parishes, etc.

    Data fields

    1. id: int(11)
    2. title: varchar(255)
    3. country_sub_id: int(11)
    4. country_id: int(11)
    5. count: int(11)
  • country_sub_sub_sub
    Records:15,288

    Sub-sub-sub-national entities.

    Data fields

    1. id: int(11)
    2. title: varchar(255)
    3. country_sub_sub_id: int(11)
    4. country_sub_id: int(11)
    5. country_id: int(11)
    6. count: int(11)
  • country_sub_sub_sub_to_hotel
    Records:118,452

    Relationship table for sub-sub-sub-national entities and hotels.

    Data fields

    1. id: int(11)
    2. hotel_id: int(11)
    3. country_sub_sub_sub_id: int(11)
  • country_sub_sub_to_hotel
    Records:293,949

    Relationship table for sub-sub-national entities and hotels.

    Data fields

    1. id: int(11)
    2. hotel_id: int(11)
    3. country_sub_sub_id: int(11)
  • country_sub_to_hotel
    Records:576,180

    Relationship table for sub-national entities and hotels.

    Data fields

    1. id: int(11)
    2. hotel_id: int(11)
    3. country_sub_id: int(11)
  • country_sub_type
    Records:613

    Different types of sub-national entities by country.

    Data fields

    1. id: int(11)
    2. title: varchar(255)
    3. country_id: int(11)
  • hotel
    Records:337,187

    The primary table of this database that contains all the hotel data. Each record is associated with a variety of records from other tables.

    Data fields

    1. id: int(11)
    2. title: varchar(255)
    3. hotel_name: varchar(255)
    4. slug: varchar(255)
    5. country_sub_id: int(11)
    6. address_full: varchar(255)
    7. address_short: varchar(255)
    8. locations: varchar(255)
    9. email: varchar(255)
    10. website: varchar(255)
    11. phone: varchar(255)
    12. fax: varchar(255)
    13. longitude: varchar(255)
    14. latitude: varchar(255)
    15. star_rating: varchar(255)
    16. star_self_rated: varchar(255)
    17. rooms: varchar(255)
    18. local_currency_code: varchar(255)
    19. price_usd: varchar(255)
    20. price_from: varchar(255)
    21. check_in: varchar(255)
    22. check_out: varchar(255)
    23. property_type_id: int(11)
    24. chain_id: int(11)
    25. rating_overall: varchar(255)
    26. rating_overall_text: varchar(255)
    27. rating_cleanliness: varchar(255)
    28. rating_dining: varchar(255)
    29. rating_facilities: varchar(255)
    30. rating_location: varchar(255)
    31. rating_rooms: varchar(255)
    32. rating_service: varchar(255)
    33. rating_points: varchar(255)
    34. reviews_count: varchar(255)
    35. reviews_summary_positive: text
    36. reviews_summary_negative: text
    37. description: mediumtext
    38. FAQ: mediumtext
    39. images_count: int(10) unsigned
  • hotel_feature
    Records:177

    The variety of different accommodation features that hotels may or may not have.

    Data fields

    1. id: int(11)
    2. title: varchar(127)
    3. type: varchar(63)
  • hotel_feature_to_hotel
    Records:6,074,492

    Each hotel has one or more features.

    Data fields

    1. id: int(11)
    2. hotel_id: int(11)
    3. hotel_feature_id: int(11)
  • hotel_feature_type
    Records:5

    Types of hotel features.

    Data fields

    1. id: int(11)
    2. title: varchar(63)
  • hotel_image
    Records:3,723,510

    Images catalog of the hotel rooms, facilities, views, etc., referencing the image files by the path field. 50,645 of the hotels, or 15%, have no images.

    Data fields

    1. id: int(11)
    2. title: varchar(255)
    3. dir: varchar(255)
    4. path: varchar(255)
    5. file_size_bytes: int(10) unsigned
    6. width_px: int(10) unsigned
    7. height_px: int(10) unsigned
    8. hotel_id: int(11)
  • location
    Records:21,359

    Independent table of important locations / visit-worthy destinations by names, longitudes and latitudes. You can calculate the distance from each hotel to any of them.

    Data fields

    1. id: int(11)
    2. title: varchar(255)
    3. slug: varchar(255)
    4. location_type_id: int(11)
    5. latitude: varchar(255)
    6. longitude: varchar(255)
  • location_type
    Records:16

    Different types of locations, associated with each location in the location table.

    Data fields

    1. id: int(11)
    2. title: varchar(255)
    3. slug: varchar(255)
  • place_of_interest
    Records:3,319,923

    Relationship table for places of interest and hotels, with names, longitudes and latitudes.

    Data fields

    1. id: int(11)
    2. longitude: varchar(255)
    3. latitude: varchar(255)
    4. name: varchar(255)
    5. hotel_id: int(11)
  • place_of_interest_name
    Records:18,560

    Places of interest across the world, by unique names.

    Data fields

    1. id: int(11)
    2. title: varchar(255)
  • property_type
    Records:10

    Different types of hotel property, associated with each hotel.

    Data fields

    1. id: int(11)
    2. title: varchar(255)
    3. slug: varchar(255)

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Prospective Applications / Implementations:

  • Global hotels comparison site
  • Travel site / community
  • Hotels online booking site
  • Hotels affiliate program site
  • Hotels search and booking application for mobile devices

Other Available Formats:

Some of these formats are available on extra charge, depending on the database.

  • Plain CSV
  • CSV for Microsoft Excel
  • Microsoft Excel .XLS file (2008, 2007, 2003, 2000)
  • Microsoft Word .DOC file (2008, 2007, 2003, 2000)
  • LaTeX
  • Open Document Spreadsheet
  • Open Document Text
  • PDF
  • XML
  • YAML
  • WordPress Category / Post Database
  • Single Table Format

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