We extract property listings, availability calendars, seasonal pricing, and host profiles from Traum-Ferienwohnungen. 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 Property Listings objects from traum-ferienwohnungen.de. All fields typed and schema-versioned.
"property_id": "123456", "title": "Ferienhaus Meerblick", "property_type": "House", "location": "Sylt, Germany", "max_guests": 4, "bedrooms": 2, "bathrooms": 1, "living_space_sqm": 85
| # | property_id | title | property_type | location | coordinates | max_guests |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Availability Calendar objects from traum-ferienwohnungen.de. All fields typed and schema-versioned.
"property_id": "123456", "date": "2024-07-15", "status": "available", "price_per_night": 120.0, "min_stay": 7, "check_in_allowed": true, "check_out_allowed": true
| # | property_id | date | status | price_per_night | min_stay | check_in_allowed |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Pricing & Fees objects from traum-ferienwohnungen.de. All fields typed and schema-versioned.
"property_id": "123456", "base_price": 120.0, "cleaning_fee": 80.0, "deposit": 200.0, "pet_fee": 15.0, "tourist_tax": 2.5, "extra_guest_fee": 10.0
| # | property_id | base_price | cleaning_fee | deposit | pet_fee | tourist_tax |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Host Profiles objects from traum-ferienwohnungen.de. All fields typed and schema-versioned.
"host_id": "H-9876", "host_name": "Sylt Vermietungen GmbH", "host_type": "Agency", "response_rate": 98, "response_time": "within 1 hour", "languages": "['German', 'English']", "total_properties": 45
| # | host_id | host_name | host_type | response_rate | response_time | languages |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Reviews objects from traum-ferienwohnungen.de. All fields typed and schema-versioned.
"review_id": "R-55432", "property_id": "123456", "guest_name": "Thomas Müller", "rating_overall": 4.8, "rating_cleanliness": 5.0, "rating_location": 5.0, "review_text": "Wunderschönes Haus...", "travel_date": "2023-08"
| # | review_id | property_id | guest_name | rating_overall | rating_cleanliness | rating_location |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our scraper handles the complexities of the DACH vacation rental market: asynchronous calendar hydration, complex fee structures, and regional search pagination.
Title, description, max guests, bedrooms, sqm, and location extracted at the listing level.
Scrape date-level availability status, minimum stay requirements, and seasonal pricing blocks.
Parse structured equipment lists (Ausstattung) including WiFi, pool, parking, and pet policies.
Capture overall scores, sub-category ratings (cleanliness, location), and full review text.
Extract agency names, response rates, and language capabilities from host profiles.
Separate base prices from cleaning fees, deposits, and local tourist taxes (Kurtaxe).
Extract latitude and longitude coordinates for precise mapping and spatial analysis.
Capture high-resolution image URLs and gallery sequences for property validation.
Monitor availability calendars daily and only emit records when dates change status from open to booked.
Brief in. Clean data out.
Provide target regions, property URLs, or host IDs. We design the extraction schema together.
We configure Scrapy crawlers, XHR interception for calendars, and proxy rotation for DACH endpoints.
Schema validation, null-rate checks, and calendar integrity testing before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Traum-Ferienwohnungen requires specific handling for asynchronous data loads and regional rate limits. Here is how we maintain stable extraction.
The availability calendar loads via asynchronous XHR requests. We intercept these payloads directly to extract clean date arrays, bypassing complex DOM parsing for pricing and booking status.
We route requests through German, Austrian, and Swiss residential IPs to avoid geo-blocking and rate limits on the search endpoints, ensuring localised pricing is displayed correctly.
Property pages frequently update their DOM structure for seasonal campaigns. We use resilient XPath fallbacks and structured data extraction to maintain schema stability.
We hash the calendar state per property. Subsequent runs only push diffs when availability or pricing changes, reducing downstream processing load.
Extracting 365-day calendars across 100,000+ properties requires distributed queue management. Our Airflow clusters optimise concurrency to meet strict delivery SLAs.
OTA aggregators and market analysts track inventory growth and regional saturation across European vacation hubs.
Property managers monitor competitor pricing strategies, seasonal rate adjustments, and minimum stay rules.
Correlate calendar availability drops with booking velocity to estimate regional occupancy rates.
Identify professional property management agencies expanding their portfolios based on host IDs.
Real estate investors analyse yield potential by combining base prices, cleaning fees, and historical occupancy data.
ML teams train models to quantify the price premium of specific amenities in specific regions.
"Traum-Ferienwohnungen holds critical supply and pricing data for the DACH vacation rental market, but its calendar endpoints require specialised interception to query at scale."
Extracting vacation rental data requires more than basic HTTP requests. You need to handle asynchronous calendar hydration, parse complex fee structures, and rotate German residential proxies to maintain access. DataFlirt manages this infrastructure entirely, delivering structured availability and pricing feeds directly to your data warehouse.
Everything supported by our traum-ferienwohnungen.de scraper — rendered SPA elements, auth walls, rate-limit evasion and beyond.
Open-source tooling on proven cloud infra — no vendor lock-in, full observability.
Handle complex property pages and intercept backend API calls for pricing and availability data directly from the network layer.
Route traffic through DACH-region residential proxies to ensure consistent access and localised pricing display.
Distributed Airflow workers manage high-concurrency calendar checks, storing state in managed PostgreSQL.
Data delivered to where your team already works — no new tooling required.
About traum-ferienwohnungen.de scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available listing and calendar data is generally permissible. We do not bypass authentication to extract private host data.
We intercept the asynchronous API calls the site makes to render the calendar, extracting the raw JSON availability and pricing data directly.
Yes. We maintain a state hash for each property's calendar and can emit diffs when dates switch from available to booked.
Yes. We separate base nightly rates from cleaning fees (Endreinigung), tourist taxes (Kurtaxe), and pet fees.
We can target specific regions (e.g., Baltic Sea, North Sea, Bavaria) or extract the entire global catalogue available on the platform.
Calendar pipelines typically run on a daily cadence, ensuring occupancy signals are up to date for pricing models.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off regional extraction or a continuous availability feed across 100,000 properties — we scope, build, and operate the pipeline.
