We extract flight schedules, dynamic pricing, fare families, seat availability, and route intelligence from Etihad. 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 Flight Schedules objects from etihad.com. All fields typed and schema-versioned.
"flight_number": "EY11", "origin_code": "AUH", "destination_code": "LHR", "departure_time": "2024-11-15T02:15:00Z", "arrival_time": "2024-11-15T06:20:00Z", "duration_minutes": 425, "aircraft_type": "Airbus A380-800", "stops": 0
| # | flight_number | origin_code | destination_code | departure_time | arrival_time | duration_minutes |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Fare Pricing objects from etihad.com. All fields typed and schema-versioned.
"flight_number": "EY11", "departure_date": "2024-11-15", "currency": "AED", "base_fare": 2150.0, "taxes_fees": 450.0, "total_price": 2600.0, "fare_family": "Economy Choice", "cabin_class": "Economy"
| # | flight_number | departure_date | currency | base_fare | taxes_fees | total_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Seat Availability objects from etihad.com. All fields typed and schema-versioned.
"flight_number": "EY11", "departure_date": "2024-11-15", "cabin_class": "Business", "seats_remaining": 4, "pitch_inches": 73, "width_inches": 20, "layout": "1-2-1"
| # | flight_number | departure_date | cabin_class | seats_remaining | seat_map_url | pitch_inches |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Route Network objects from etihad.com. All fields typed and schema-versioned.
"origin_code": "AUH", "destination_code": "JFK", "direct_flight": true, "frequency_per_week": 7, "days_of_week": "['Mon', 'Tue', 'Wed', 'Thu', 'Fri', 'Sat', 'Sun']", "distance_miles": 6867
| # | origin_code | destination_code | direct_flight | frequency_per_week | days_of_week | distance_miles |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Etihad Guest objects from etihad.com. All fields typed and schema-versioned.
"flight_number": "EY11", "cabin_class": "Economy", "tier": "Gold", "miles_earned": 3400, "tier_miles": 3400, "bonus_miles": 1700, "redemption_availability": true
| # | flight_number | cabin_class | tier | miles_earned | tier_miles | bonus_miles |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Etihad scraper navigates complex booking flows, dynamic pricing matrices, and multi-currency displays. We handle session management and anti-bot circumvention natively.
Capture departure times, arrival times, aircraft types, layover durations, and operating carrier details for any route.
Extract base fares, taxes, and total prices across Economy, Business, and First class cabins. Timestamped for accurate price history.
Map pricing to Etihad specific fare families like Economy Value, Choice, and Flex. Capture cancellation and change rules.
Scrape pricing data from different Point of Sale (POS) regions to identify geographical price discrimination and currency anomalies.
Extract the 7-day or 30-day flexible date pricing matrices to build comprehensive demand and pricing curves.
Extract cabin baggage allowances, checked baggage weight limits, and extra baggage costs per fare class.
Identify flights marketed by Etihad but operated by partners. Extract the true operating carrier and metal.
Extract miles earned per flight and tier, along with redemption seat availability and associated taxes.
Run pipelines at hourly cadences for high-priority routes to detect yield management changes and flash sales.
Brief in. Clean data out.
Provide origin-destination pairs, date ranges, and POS requirements. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for etihad.com.
Schema validation, null-rate checks, price-outlier detection, and timezone standardisation before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Airlines use sophisticated bot mitigation to protect their pricing engines. Here is how we maintain reliable access to etihad.com.
Airline websites require sequential requests with strict token passing. We maintain persistent Playwright sessions that mimic human booking flows, ensuring valid token generation for pricing API calls.
Pricing varies by POS. We use residential proxies located in the target market (e.g., UAE, UK, US) to retrieve localized pricing and avoid datacenter IP bans.
Etihad loads pricing data asynchronously. Our Playwright nodes wait for specific XHR network idleness and DOM mutations before extracting the final fare values.
Aggressive scraping triggers immediate blocks from airline CDNs. We implement jittered request delays and distribute crawls across wide IP pools to stay below detection thresholds.
We normalise timezones to UTC, convert flight durations to standard minutes, and map aircraft types to standard IATA codes for immediate warehouse usability.
Online Travel Agencies (OTAs) and metasearch engines monitor direct-channel pricing to ensure parity and optimise their own markups.
Rival airlines track Etihad's fare adjustments, flash sales, and route expansions to inform their own yield management strategies.
Enterprise travel managers audit booked fares against public availability to ensure travel management companies deliver best logical fares.
Aviation analysts monitor seat availability and price escalation curves to model route profitability and load factors.
Travel tech startups ingest structured schedule and pricing data to power autonomous booking agents and itinerary planners.
Points aggregators track Etihad Guest redemption availability and upgrade costs to alert users to high-value reward flights.
"Airline pricing is notoriously volatile and heavily guarded. Accessing structured, real-time fare data requires infrastructure that treats every request like a genuine booking flow."
Extracting data from etihad.com involves navigating complex session states, asynchronous pricing APIs, and aggressive CDN bot protection. DataFlirt manages this entire lifecycle. We handle the residential proxies, the browser fingerprinting, and the schema maintenance, delivering clean, normalised aviation data directly to your warehouse.
Everything supported by our etihad.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 route orchestration and deduplication. Playwright handles complex booking flows, session cookies, and JS execution for pricing APIs.
We maintain pools of residential ISP proxies to simulate genuine Point of Sale locations. Rotation happens per session to maintain token validity.
Pipelines run on Kubernetes. Airflow handles scheduling, dependency management, and SLA alerting. All state stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About etihad.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available flight schedules and pricing is generally permissible. DataFlirt targets only public, non-authenticated data. We do not extract personal passenger data or circumvent authentication walls. Clients should review 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 maintain session state precisely as a standard browser would during a booking flow.
Yes. We route requests through residential proxies located in the target country to ensure you receive the accurate localized pricing and currency.
We can configure pipelines to run at custom cadences. High-priority routes can be scraped hourly, while broad network sweeps typically run daily. Delivery occurs immediately after extraction.
Every pipeline run produces timestamped snapshots. We maintain a time-series table per route from the date your pipeline starts. We do not hold historical data prior to pipeline commissioning.
Our smallest packages start at a defined list of 100 origin-destination pairs with daily delivery. Pricing scales based on route volume, extraction frequency, and POS requirements. Contact us for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily snapshot of key routes or continuous price monitoring across the entire network, we scope, build, and operate the pipeline. Tell us what you need.
