We extract dynamic pricing, routes, schedules, and operator data across trains, buses, flights, and ferries from Omio. 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 Train Routes objects from omio.com. All fields typed and schema-versioned.
"journey_id": "TRN-8849201", "departure_station": "Berlin Hauptbahnhof", "arrival_station": "München Hauptbahnhof", "departure_time": "2026-08-14T08:30:00Z", "duration_minutes": 245, "price": 89.9, "currency": "EUR", "operator": "Deutsche Bahn"
| # | journey_id | departure_station | arrival_station | departure_time | arrival_time | duration_minutes |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Bus Schedules objects from omio.com. All fields typed and schema-versioned.
"journey_id": "BUS-99210", "origin_city": "Paris", "destination_city": "Amsterdam", "departure_time": "2026-08-15T22:00:00Z", "duration_minutes": 480, "operator": "FlixBus", "price": 34.5, "currency": "EUR"
| # | journey_id | origin_city | destination_city | departure_time | arrival_time | duration_minutes |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Flight Pricing objects from omio.com. All fields typed and schema-versioned.
"journey_id": "FLT-4412", "origin_airport": "LHR", "destination_airport": "BER", "flight_number": "BA990", "airline": "British Airways", "price": 145.0, "currency": "GBP", "baggage_included": false
| # | journey_id | origin_airport | destination_airport | flight_number | airline | departure_time |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Multi-Modal Journeys objects from omio.com. All fields typed and schema-versioned.
"journey_id": "MM-77382", "origin": "London St Pancras", "destination": "Barcelona Sants", "total_duration_minutes": 680, "total_price": 210.0, "currency": "GBP", "operators": "['Eurostar', 'SNCF']", "co2_emissions_kg": 12.4
| # | journey_id | origin | destination | total_duration_minutes | segments | total_price |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Stations & Stops objects from omio.com. All fields typed and schema-versioned.
"station_id": "STN-1092", "name": "Milano Centrale", "type": "train_station", "city": "Milan", "country": "Italy", "latitude": 45.4854, "longitude": 9.2038
| # | station_id | name | type | city | country | latitude |
|---|---|---|---|---|---|---|
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Our Omio scraper handles every layer of the platform: multi-modal routing, dynamic pricing, operator mapping, and station geolocation. Built with JavaScript rendering, session management, and anti-bot circumvention.
Extract schedules, pricing, train numbers, and transfer nodes for major European operators like Deutsche Bahn, SNCF, Trenitalia, and Renfe.
Capture long-distance bus routes, departure points, durations, and pricing across carriers like FlixBus and ALSA.
Monitor airline ticket prices, baggage rules, and flight numbers for intra-European and global routes.
Scrape ferry schedules, vehicle transport options, and passenger pricing for Mediterranean and Nordic routes.
Map complex journeys combining multiple transport types, including transfer wait times and segment-specific operators.
Track price fluctuations across different booking windows, capturing base fares and mandatory fees.
Extract precise latitude and longitude coordinates for train stations, bus stops, and airports.
Capture estimated carbon footprints for different journey options to support sustainability reporting.
Run one-off route exports or configure continuous pipelines at hourly or daily cadences.
Brief in. Clean data out.
Provide origin-destination pairs, travel dates, or transport modes. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for omio.com.
Schema validation, null-rate checks, price-outlier detection, and route sampling before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Travel aggregators invest heavily in scraping detection and rate limiting. Here is how we stay resilient.
Omio requires complex interactions with date pickers, autocomplete location fields, and passenger selectors. We run full Playwright browser sessions to execute these searches accurately.
Search results on Omio are tied to session tokens and XHR polling. Our crawlers manage token lifecycles and handle the asynchronous polling required to wait for all operator results to load.
Aggressive rate limiting blocks data centre IPs instantly. Our infrastructure routes requests through residential ISP proxies in the target region, maintaining valid browser fingerprints.
Transport data spans multiple timezones and currencies. We normalise all timestamps to UTC and standardise currency codes to ensure your downstream analytics are accurate.
Omio frequently updates its frontend components. We use multiple fallback chains per field, extracting data from hidden JSON objects and API responses where possible to avoid DOM fragility.
Online Travel Agencies monitor Omio to benchmark pricing, identify route gaps, and adjust their own dynamic pricing models.
Train and bus operators track competitor schedules, pricing, and route durations to optimise their own network planning.
Urban planners and mobility startups analyse multi-modal transfer nodes and journey times to identify underserved corridors.
Sustainability platforms extract CO2 emission data across different transport modes to build accurate enterprise travel reporting tools.
Private equity firms track operator route coverage, pricing power, and market share to evaluate transport sector investments.
Meta-search engines use structured Omio data to augment their own routing algorithms and provide multi-modal alternatives.
"Omio aggregates the most fragmented transport network in the world. Standardising that data requires parsing thousands of operator-specific logic rules."
Most teams underestimate the complexity of scraping multi-modal travel data. Omio relies on heavy client-side rendering, session-locked search tokens, and aggressive rate limits. DataFlirt absorbs that infrastructure overhead so your analysts can focus on route optimisation and price parity, not maintaining CAPTCHA solvers.
Everything supported by our omio.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, search form inputs, and XHR polling.
We maintain pools of residential ISP proxies across EU regions. Rotation happens per-request with sticky sessions where required for search tokens.
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 omio.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available travel schedules and pricing is generally permissible. DataFlirt targets only public, non-authenticated route data. We do not extract personal data or circumvent authentication walls. Clients should review terms of service and consult legal counsel for specific use cases.
Omio uses asynchronous XHR polling to load results from multiple operators over several seconds. Our Playwright scripts monitor network traffic and wait for the polling cycle to complete before extracting the final DOM state.
Yes. You provide the origin, destination, and target travel dates. We parameterise the pipeline to execute searches for those exact parameters across any future booking window.
Yes. Multi-modal journeys include segment-level data. We calculate and extract the wait time between segments, as well as any required station changes.
Pricing on Omio is highly dynamic. We can configure pipelines to run at hourly intervals for high-priority routes, ensuring your price intelligence models are fed with near real-time data.
Yes. We provide a sample run of up to 100 origin-destination pairs as part of the scoping process. This allows you to validate schema fit and data quality before committing.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off route map or continuous price monitoring across thousands of European connections, we scope, build, and operate the pipeline.
