We extract flight schedules, dynamic pricing, Megavolotea member fares, baggage fees, and seat selection costs from Volotea. 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 volotea.com. All fields typed and schema-versioned.
"flight_number": "V7 2514", "origin_iata": "NTE", "destination_iata": "PMI", "departure_time": "2026-06-15T08:30:00Z", "arrival_time": "2026-06-15T10:15:00Z", "duration_minutes": 105, "aircraft_type": "A319", "operating_carrier": "Volotea"
| # | flight_number | origin_iata | destination_iata | departure_time | arrival_time | duration_minutes |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Fares objects from volotea.com. All fields typed and schema-versioned.
"flight_number": "V7 2514", "standard_fare": 45.99, "megavolotea_fare": 29.99, "currency": "EUR", "tax_amount": 12.5, "base_fare": 33.49, "available_seats": 4, "fare_class": "Economy"
| # | flight_number | departure_date | standard_fare | megavolotea_fare | currency | tax_amount |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Ancillary Fees objects from volotea.com. All fields typed and schema-versioned.
"flight_number": "V7 2514", "cabin_bag_fee": 24.0, "checked_bag_10kg_fee": 35.0, "checked_bag_20kg_fee": 45.0, "standard_seat_fee": 6.0, "front_row_seat_fee": 18.0, "priority_boarding": 12.0
| # | flight_number | route | cabin_bag_fee | checked_bag_10kg_fee | checked_bag_20kg_fee | standard_seat_fee |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Route Network objects from volotea.com. All fields typed and schema-versioned.
"origin_iata": "NTE", "destination_iata": "PMI", "country_origin": "France", "country_destination": "Spain", "distance_km": 845, "frequency_per_week": 4, "season_start": "2026-04-01", "season_end": "2026-10-31"
| # | origin_iata | destination_iata | country_origin | country_destination | distance_km | frequency_per_week |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Calendar Pricing objects from volotea.com. All fields typed and schema-versioned.
"origin_iata": "NTE", "destination_iata": "PMI", "flight_date": "2026-06-15", "lowest_fare": 45.99, "currency": "EUR", "is_promo": false, "days_to_departure": 42, "extraction_date": "2026-05-04T12:00:00Z"
| # | origin_iata | destination_iata | flight_date | lowest_fare | currency | is_promo |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Volotea scraper handles every layer of the booking engine: standard pricing, Megavolotea tiers, ancillary costs, and route network discovery. JavaScript rendering, session management, and anti-bot circumvention are built directly into the pipeline.
Flight numbers, departure times, arrival times, aircraft types, and operating carriers extracted across the entire Volotea network.
Capture base fares, tax breakdowns, and final prices. Timestamped per crawl to track yield management adjustments.
Extract both standard passenger fares and discounted Megavolotea member prices side by side for margin analysis.
Scrape dynamic fees for cabin baggage, checked luggage, seat selection, and priority boarding across different routes.
Traverse monthly calendar views to extract the lowest available fares across a 30-day window in a single pass.
Monitor the Volotea route map for new seasonal additions, frequency changes, and route cancellations.
Extract pricing in EUR, GBP, or other supported currencies based on point of sale configuration.
Capture low stock warnings and remaining seat counts to estimate load factors and booking velocity.
Run one-off bulk exports or configure continuous pipelines at hourly or daily cadences with change detection.
Brief in. Clean data out.
Provide origin destination pairs, date ranges, or full network requirements. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for volotea.com.
Schema validation, null-rate checks, price outlier detection, and sample routes before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Airlines invest heavily in scraping detection to protect their pricing data. Here is how we stay resilient and why teams choose managed infrastructure over DIY.
Airline bot detection operates on TLS fingerprints, browser headers, and IP reputation. Our crawlers use residential ISP proxies with realistic browser fingerprints and full cookie session management trained on real user behaviour patterns.
Volotea booking flows require sequential session tokens to access pricing and ancillary steps. We manage full stateful sessions, passing required headers and cookies to ensure the booking engine returns valid data.
Extracting calendar matrices requires interacting with heavily JavaScript-rendered components. We run full Playwright browser sessions to trigger lazy loading and hydrate dynamic price widgets.
Airlines change their DOM structure frequently. Our selector strategy uses multiple fallback chains per field, including CSS selectors, XPath, and XHR interception, so a layout change does not break your data pipeline.
For large route networks, we maintain a hash index of last-seen values per flight. Subsequent runs only push diffs, reducing compute cost, storage bloat, and downstream processing load.
Rival airlines monitor Volotea base fares and Megavolotea discounts to optimise their own pricing strategies on overlapping routes.
Online travel agencies ingest scheduled flights and pricing to populate their own search engines and booking interfaces.
Revenue management teams analyse how Volotea adjusts prices closer to departure dates to refine their own yield management algorithms.
Consultancies and airlines track baggage and seat fees to understand the total cost of travel and benchmark ancillary revenue strategies.
Airport authorities and network planners track Volotea route additions and frequency changes to identify regional demand trends.
Financial analysts use aggregate fare data to track inflation metrics within the European low-cost aviation sector.
"Volotea operates a highly dynamic pricing model across European regional routes. Tracking their base fares and ancillary fees requires infrastructure built specifically for airline booking engines."
Most teams underestimate the investment required. Reliable airline scraping requires residential proxies, full JavaScript rendering, session token management, and continuous anomaly monitoring. DataFlirt absorbs that complexity so your engineers can focus entirely on the analysis, rather than maintaining infrastructure.
Everything supported by our volotea.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, deduplication, and retry logic. Playwright handles JavaScript rendering, cookie sessions, and interaction flows. Combined via custom middleware.
We maintain pools of residential ISP proxies across EU regions. Rotation happens per session with sticky IPs where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, dependency management, and SLA alerting. All state is stored securely in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About volotea.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available pricing and route information from Volotea is generally permissible under applicable law for non-disruptive use cases. DataFlirt targets only public, non-authenticated flight data. We do not extract personal passenger data or circumvent authentication walls. Clients should review the Volotea 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 manage session tokens meticulously and solve challenges using automated APIs when required.
Yes. Volotea displays Megavolotea member pricing alongside standard fares on public search results. We extract both data points simultaneously so you can compare the discount margins.
Real-time streaming pipelines achieve sub-60-minute latency for price and availability signals on defined route sets. Full network refreshes at daily cadence complete within a dedicated window. Historical snapshots are available from the day your pipeline is commissioned.
Yes. Ancillary fees are dynamic and vary by route. We progress the booking flow to the ancillary selection steps to extract accurate costs for cabin bags, checked luggage, and seat assignments.
Our smallest packages start at a defined route list with daily delivery. For full network coverage or custom schema requirements, we price based on volume and delivery frequency. Contact us with your use case for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off route network dump or a continuous price-monitoring feed across European destinations, we scope, build, and operate the pipeline. Tell us what you need.
