We extract flight itineraries, dynamic pricing, hotel rates, Hacker Fares, and car rental inventory from Kayak. Delivered as clean JSON, CSV, or Parquet to S3, BigQuery, or Snowflake 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 Flights objects from kayak.com. All fields typed and schema-versioned.
"origin": "LHR", "destination": "JFK", "departure_time": "2026-08-12T08:30:00Z", "arrival_time": "2026-08-12T11:15:00Z", "airline": "British Airways", "flight_number": "BA117", "price": 482.5, "currency": "GBP", "stops": 0, "hacker_fare": false
| # | origin | destination | departure_time | arrival_time | airline | flight_number |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Hotels objects from kayak.com. All fields typed and schema-versioned.
"property_name": "The Plaza", "location": "New York City, NY", "star_rating": 5.0, "guest_rating": 9.2, "review_count": 3412, "price_per_night": 850.0, "currency": "USD", "provider": "Booking.com"
| # | property_name | location | star_rating | guest_rating | review_count | price_per_night |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Car Rentals objects from kayak.com. All fields typed and schema-versioned.
"pickup_location": "JFK Airport", "car_type": "Midsize SUV", "agency": "Hertz", "transmission": "Automatic", "price_per_day": 64.0, "total_price": 448.0, "currency": "USD", "mileage_policy": "Unlimited"
| # | pickup_location | dropoff_location | car_type | agency | capacity | transmission |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Packages objects from kayak.com. All fields typed and schema-versioned.
"destination": "Cancun, Mexico", "flight_included": true, "hotel_included": true, "duration_days": 7, "total_price": 1250.0, "currency": "USD", "departure_date": "2026-11-01", "return_date": "2026-11-08"
| # | package_id | destination | flight_included | hotel_included | duration_days | total_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Providers objects from kayak.com. All fields typed and schema-versioned.
"provider_name": "Expedia", "provider_type": "OTA", "base_fare": 410.0, "taxes_fees": 72.5, "total_fare": 482.5, "currency": "GBP", "baggage_included": false, "cancellation_policy": "Non-refundable"
| # | provider_name | provider_type | booking_url | base_fare | taxes_fees | total_fare |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Kayak scraper handles every layer of the platform: flight matrices, dynamic hotel pricing, Hacker Fares, and aggregator redirects - with JavaScript rendering, session management, and anti-bot circumvention built in.
Origin, destination, dates, airlines, layovers, and cabin classes - scraped across millions of route combinations.
Identify split tickets across different airlines that Kayak bundles into single itineraries for cheaper fares.
Extract pricing across multiple OTAs, room types, and cancellation policies for global properties.
Extract prices from specific Point of Sale (POS) regions to track geo-dependent pricing discrepancies.
Differentiate base fares from total fares including taxes, fees, and checked baggage allowances.
Track agencies, vehicle types, pickup locations, and daily rates across major airports and cities.
Capture complex itineraries and multi-leg pricing structures that standard OTA APIs omit.
Capture deep links to the actual booking OTAs and airline websites from Kayak's interface.
Run daily global crawls or configure continuous hourly pipelines for high-volatility route monitoring.
Brief in. Clean data out.
Provide airport pairs, dates, hotel IDs, or car rental locations. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, and CAPTCHA handling for kayak.com.
Schema validation, null-rate checks, and price-outlier detection before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Travel aggregators heavily protect their pricing data. Here is how we stay resilient - and why teams choose managed infrastructure over DIY.
Travel aggregators use aggressive bot detection. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management.
Kayak flight results are heavily JavaScript-rendered. We run full Playwright browser sessions with JavaScript execution and lazy-load triggering to capture full matrices.
Prices change based on where the user searches from. We route requests through specific regional proxies to capture accurate local pricing and currency data.
Kayak frequently tests new UI layouts. Our selector strategy uses fallback chains to ensure a layout change does not break your data pipeline.
Every run emits structured logs. We alert on null-rate spikes, missing routes, and coverage drops - and respond before you notice.
OTAs and airlines monitor their placement and pricing against competitors on aggregator platforms.
Airlines track competitor pricing on specific routes to optimise their own dynamic pricing models.
Analysts track route profitability, new airline launches, and seasonal demand fluctuations.
Travel management companies track average fares to build accurate client budgets and policy caps.
ML teams use historical flight pricing datasets to train fare prediction and recommendation engines.
Travel agencies identify Hacker Fares and ticketing anomalies to build cheaper custom itineraries.
"Kayak aggregates the world's travel inventory into a single interface, but extracting that pricing matrix at scale requires serious infrastructure."
Most teams underestimate the investment required: reliable Kayak scraping requires global residential proxies, full JavaScript rendering, CAPTCHA handling, and anomaly monitoring. DataFlirt absorbs that complexity so your engineers can focus on the analysis - not the infrastructure.
Everything supported by our kayak.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 and interaction flows for flight searches.
We maintain pools of residential ISP proxies across global regions. Rotation happens per-request to simulate diverse user traffic.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About kayak.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available pricing information from Kayak is generally permissible under applicable law. DataFlirt targets only public, non-authenticated flight and hotel data. We do not extract personal data or circumvent authentication walls.
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 route requests through residential proxies located in your target countries to capture Point-of-Sale dependent pricing accurately.
Real-time streaming pipelines achieve sub-60-minute latency for price signals on a defined route set. Full catalogue refreshes complete within a 6-12 hour window depending on size.
Yes. We identify and extract split-ticket itineraries, detailing the individual legs and respective airlines that make up the Hacker Fare.
Our smallest packages start at a defined route list (e.g., 5,000 airport pairs) with daily delivery. Contact us with your use case for a scoped quote.
Absolutely. We provide a sample run of up to 100 routes or hotel searches as part of the pre-engagement scoping process.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off hotel rate dump or a continuous price-monitoring feed across 100,000 flight routes - we scope, build, and operate the pipeline. Tell us what you need.
