We extract hotel listings, flight itineraries, dynamic pricing signals, availability calendars, and reviews from Orbitz. Delivered as clean JSON, CSV, or Parquet to S3 or BigQuery on your cadence.
Structured, schema-consistent data across all major object types — delivered clean, typed, and ready to query.
Complete list of extractable fields for Hotel Listings objects from orbitz.com. All fields typed and schema-versioned.
"hotel_id": "719284", "name": "The Ritz-Carlton, Chicago", "star_rating": 5.0, "city": "Chicago", "price_per_night": 450.0, "currency": "USD", "review_score": 9.4, "review_count": 1205
| # | hotel_id | name | star_rating | address | city | country |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Flight Itineraries objects from orbitz.com. All fields typed and schema-versioned.
"airline": "United Airlines", "flight_number": "UA412", "departure_airport": "ORD", "arrival_airport": "LHR", "price": 850.0, "currency": "USD", "stops": 0, "cabin_class": "Economy"
| # | flight_id | airline | flight_number | departure_airport | arrival_airport | departure_time |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Car Rentals objects from orbitz.com. All fields typed and schema-versioned.
"provider": "Hertz", "car_type": "Midsize SUV", "transmission": "Automatic", "daily_rate": 55.0, "total_price": 275.0, "currency": "USD", "unlimited_mileage": true
| # | rental_id | provider | car_type | seats | transmission | pickup_location |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Reviews & Ratings objects from orbitz.com. All fields typed and schema-versioned.
"review_id": "REV982374", "hotel_id": "719284", "review_date": "2026-03-14", "overall_score": 10.0, "review_title": "Exceptional stay in downtown", "review_text": "The service was impeccable and the views were stunning.", "travel_type": "Couples"
| # | review_id | hotel_id | reviewer_name | review_date | overall_score | cleanliness_score |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Vacation Packages objects from orbitz.com. All fields typed and schema-versioned.
"package_id": "PKG4412", "destination": "Cancun, Mexico", "hotel_name": "Secrets The Vine Cancun", "airline": "American Airlines", "total_price": 1250.0, "currency": "USD", "discount_amount": 150.0
| # | package_id | destination | start_date | end_date | hotel_name | airline |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Orbitz scraper handles every layer of the platform: hotel search grids, dynamic flight pricing, room availability calendars, and review corpuses with JavaScript rendering and anti-bot circumvention built in.
Extract property names, star ratings, precise coordinates, amenities, and high-resolution image URLs across any destination.
Monitor airline schedules, cabin classes, baggage policies, and real-time ticket prices across one-way or round-trip routes.
Capture granular room details including bed configurations, square footage, occupancy limits, and specific room-level pricing.
Scrape vehicle types, provider names, transmission details, and daily rates across airport and city pickup locations.
Extract full review text, sub-category scores for cleanliness and service, travel types, and review dates.
Track exact refund windows, penalty fees, and flexible booking options for flights, hotels, and rental cars.
Configure complex multi-city flight searches to extract pricing data for extended travel routes and layovers.
Capture price fluctuations over time for specific dates and destinations to build predictive pricing models.
Run one-off bulk exports or configure continuous pipelines at hourly or daily cadences with change-detection diffing.
Brief in. Clean data out.
Provide destination lists, flight routes, or hotel IDs. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for orbitz.com.
Schema validation, null-rate checks, price-outlier detection, and data sampling before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
OTA platforms invest heavily in scraping detection. Here is how we stay resilient and why teams choose managed infrastructure over DIY.
Orbitz uses advanced bot detection that operates on TLS fingerprints and browser headers. Our crawlers use residential ISP proxies with realistic browser fingerprints and full cookie session management.
Orbitz search results and availability calendars are heavily JavaScript-rendered. We run full Playwright browser sessions with lazy-load triggering and dynamic price widget hydration.
OTA platforms change their DOM structure frequently. Our selector strategy uses multiple fallback chains per field, so a layout change does not break your data pipeline overnight.
Flight and hotel searches on Orbitz expire quickly. We manage active sessions, refresh tokens automatically, and maintain state to ensure long-running extractions complete successfully.
For large hotel catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Travel agencies and competitor OTAs monitor hotel and flight pricing to optimise their own margins and promotional offers.
Hotels track their own listing positions and competitor pricing on Orbitz to adjust daily available rates.
Analysts track destination popularity, average nightly rates, and seasonal price spikes to identify investment opportunities.
Machine learning teams use historical travel pricing datasets to train forecasting models and recommendation engines.
Airlines and hospitality chains correlate search availability and price changes with overall market demand.
Car rental companies monitor daily rates and vehicle availability across specific airport locations to stay competitive.
"Orbitz holds a massive repository of real-time travel pricing and availability data, but none of it is queryable unless you build the extraction pipeline."
Most teams underestimate the investment required. Reliable OTA scraping requires residential proxies, full JavaScript rendering, CAPTCHA handling, session persistence, and anomaly monitoring. DataFlirt absorbs that complexity entirely so your engineers can focus on the analysis rather than the infrastructure.
Everything supported by our orbitz.com scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Scrapy handles crawl orchestration and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows for complex travel searches.
We maintain pools of residential ISP proxies across global regions. Rotation happens per-request with sticky sessions required for multi-step flight searches.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state is stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About orbitz.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available pricing and availability data from Orbitz is generally permissible. DataFlirt targets only public, non-authenticated travel data. We do not extract personal user data or circumvent authentication walls. Clients should review Orbitz terms of service and consult legal counsel for specific use cases.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. We monitor for CAPTCHA rate spikes in real time and trigger solver queues automatically.
Yes. We configure pipelines to search specific routes on a defined schedule, capturing real-time price fluctuations, cabin availability, and baggage fee changes over time.
Real-time streaming pipelines achieve sub-60-minute latency for price signals on a defined set of routes or hotels. Full destination refreshes at daily cadence complete within a 6-12 hour window.
Yes. We extract the full review text, overall score, sub-category ratings, reviewer details, and travel type, paginating through all available review pages for a property.
Our smallest packages start at a defined list of routes or properties with weekly delivery. For larger global catalogues, we price based on volume and delivery frequency.
Yes. We provide a sample run of up to 100 hotel properties or flight routes as part of the scoping process so you can validate schema fit and data quality before signing a contract.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off destination export or a continuous price-monitoring feed across thousands of routes, we scope, build, and operate the pipeline. Tell us what you need.
