We extract flight schedules, dynamic fare matrices, seat availability, and route networks from Jazeera Airways. 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 jazeera.com. All fields typed and schema-versioned.
"flight_number": "J9 253", "origin_iata": "KWI", "destination_iata": "DXB", "departure_time": "2026-08-14T08:30:00Z", "arrival_time": "2026-08-14T11:10:00Z", "duration_mins": 100, "aircraft_type": "Airbus A320neo", "flight_status": "Scheduled"
| # | flight_number | origin_iata | destination_iata | departure_time | arrival_time | duration_mins |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Pricing & Fares objects from jazeera.com. All fields typed and schema-versioned.
"flight_number": "J9 253", "departure_date": "2026-08-14", "fare_class": "Economy Light", "base_fare": 45.0, "taxes": 12.5, "total_price": 57.5, "currency": "KWD", "discount_applied": false
| # | flight_number | departure_date | fare_class | base_fare | taxes | total_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Seat Availability objects from jazeera.com. All fields typed and schema-versioned.
"flight_number": "J9 253", "departure_date": "2026-08-14", "cabin_class": "Economy", "seats_available": 14, "pitch_inches": 29, "width_inches": 18, "power_available": true
| # | flight_number | departure_date | cabin_class | seats_available | seat_map_url | pitch_inches |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Route Network objects from jazeera.com. All fields typed and schema-versioned.
"origin_iata": "KWI", "destination_iata": "LHR", "direct_flight": true, "frequency_per_week": 7, "seasonal_route": false, "distance_km": 4680, "flight_time_mins": 410
| # | origin_iata | destination_iata | direct_flight | frequency_per_week | seasonal_route | distance_km |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Ancillary Fees objects from jazeera.com. All fields typed and schema-versioned.
"flight_number": "J9 253", "baggage_allowance_kg": 20, "extra_baggage_fee": 15.0, "seat_selection_fee": 5.0, "meal_preorder_fee": 8.0, "priority_boarding_fee": 10.0, "currency": "KWD"
| # | flight_number | baggage_allowance_kg | extra_baggage_fee | seat_selection_fee | meal_preorder_fee | priority_boarding_fee |
|---|---|---|---|---|---|---|
| 1 | ||||||
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| 3 |
Our scraper handles the Jazeera Airways booking engine, session tokens, and dynamic pricing matrices. We bypass rate limits and deliver clean flight data.
Capture origin, destination, departure times, arrival times, and aircraft types for all active routes.
Extract base fares, taxes, and total prices across multiple fare classes and dates.
Monitor remaining seat counts and cabin class availability for specific flights.
Map direct and connecting flight routes, including frequency and seasonal variations.
Track costs for extra baggage, seat selection, meals, and priority boarding.
Extract pricing in KWD, USD, EUR, or GBP depending on your target market requirements.
Pull 30 day fare matrices to identify pricing trends and low cost travel dates.
Configure high frequency polling for specific routes to detect immediate price drops.
Run one off bulk exports or configure continuous pipelines at hourly or daily cadences.
Brief in. Clean data out.
Provide origin destination pairs, date ranges, and target currencies. We design the extraction schema together.
We configure Scrapy Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for jazeera.com.
Schema validation, null rate checks, price outlier detection, and sample routes before full launch.
JSON CSV Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Aviation booking engines use complex session management and aggressive rate limiting. Here is how we maintain stable extraction.
Airline websites block data center IPs aggressively. Our crawlers use residential ISP proxies with realistic browser fingerprints and full cookie session management.
Jazeera Airways relies on single page application frameworks for flight searches. We run full Playwright browser sessions to execute JavaScript and capture dynamic pricing.
Flight searches require valid session tokens and cookie states. Our pipeline manages these tokens automatically, ensuring search requests return valid fare data.
For large route networks, we maintain a hash index of last seen values per field. Subsequent runs only push diffs, reducing compute cost and storage bloat.
Every run emits structured logs to our observability stack. We alert on null rate spikes, price outliers, and schema drift.
Airlines and OTAs monitor Jazeera Airways pricing to adjust their own fare structures and remain competitive.
Online travel agencies ingest direct pricing and schedule data to supplement GDS feeds.
Aviation analysts track flight frequencies and pricing trends to model route profitability.
Consultancies analyse schedule density and seat capacity to estimate market share on specific Middle Eastern routes.
Revenue management teams use competitor fare data to train machine learning models for dynamic pricing.
Metasearch engines populate their results with direct scrape data to ensure price accuracy.
"Jazeera Airways operates a highly dynamic pricing model across its Middle Eastern and European routes. Capturing this data requires bypassing complex booking engine state tokens."
Aviation data extraction is notoriously difficult due to session based booking flows and aggressive rate limiting. DataFlirt manages the proxy rotation, session tokens, and calendar matrix parsing so your engineering team receives clean tabular data without maintaining brittle scrapers.
Everything supported by our jazeera.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 session tokens.
We maintain pools of residential ISP proxies across Middle Eastern and global regions to bypass rate limits.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and dependency management.
Data delivered to where your team already works — no new tooling required.
About jazeera.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available flight schedules and pricing data is generally permissible. DataFlirt targets only public, non authenticated data. We do not extract personal passenger data or circumvent authentication walls.
Our Playwright integration manages browser sessions, cookie jars, and CSRF tokens automatically, ensuring flight search requests are accepted by the backend servers.
Yes. We can iterate through the 30 day calendar views to extract the lowest available fares across a wide date range for any route.
Real time streaming pipelines achieve sub 60 minute latency for pricing updates on defined routes. Daily bulk exports complete within a 4 hour window.
Our smallest packages start at a defined route list with daily delivery. For larger networks or high frequency polling, we price based on volume and compute requirements.
Absolutely. We provide a sample run of up to 50 routes as part of the pre engagement scoping process so you can validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one off schedule export or a continuous price monitoring feed across 200 routes, we scope, build, and operate the pipeline. Tell us what you need.
