We extract detailed hardware specifications, merchant offers, shipping matrices, and price histories from Geizhals. 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 Product Specs objects from geizhals.at. All fields typed and schema-versioned.
"geizhals_id": "2815732", "name": "AMD Ryzen 7 7800X3D", "manufacturer": "AMD", "ean": "0730143314930", "lowest_price": 349.0, "offer_count": 84, "rating": 4.9
| # | geizhals_id | name | category | manufacturer | ean | release_date |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Merchant Offers objects from geizhals.at. All fields typed and schema-versioned.
"merchant_name": "Mindfactory", "price": 349.0, "shipping_cost": 8.99, "availability_status": "in stock", "delivery_time": "1-3 days", "merchant_rating": 4.8, "is_sponsored": false
| # | offer_id | geizhals_id | merchant_name | merchant_id | price | shipping_cost |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Price History objects from geizhals.at. All fields typed and schema-versioned.
"geizhals_id": "2815732", "date": "2023-10-24", "lowest_price_at": 355.5, "lowest_price_de": 349.0, "lowest_price_eu": 349.0, "merchant_count": 82
| # | geizhals_id | date | lowest_price_at | lowest_price_de | lowest_price_eu | average_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Merchant Intelligence objects from geizhals.at. All fields typed and schema-versioned.
"merchant_id": "1024", "name": "Alternate", "overall_rating": 4.6, "review_count": 14592, "positive_pct": 92, "country": "DE"
| # | merchant_id | name | overall_rating | review_count | positive_pct | neutral_pct |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Complete list of extractable fields for Category Rankings objects from geizhals.at. All fields typed and schema-versioned.
"category_name": "Processors (CPUs)", "position": 1, "geizhals_id": "2815732", "product_name": "AMD Ryzen 7 7800X3D", "lowest_price": 349.0, "trend_indicator": "stable"
| # | category_id | category_name | position | geizhals_id | product_name | lowest_price |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
| 3 |
Our Geizhals scraper navigates Cloudflare protections and regional session contexts to extract exact hardware specifications, merchant matrices, and historical pricing curves.
Extract exhaustive technical specifications, standard across Geizhals categories, mapped to unified JSON.
Capture localized pricing across Austria (.at), Germany (.de), EU, and UK (Skinflint) domains.
Scrape every merchant listing per product, including base price, shipping costs, and payment method surcharges.
Monitor real-time stock indicators and estimated delivery windows across hundreds of retailers.
Extract historical price curves and trend data directly from Geizhals' historical charting tools.
Map Geizhals listings to your internal catalogue using extracted EANs, MPNs, and manufacturer codes.
Track seller ratings, review counts, and dispute resolution metrics to vet marketplace competitors.
Scrape top-10 rankings and trending products within highly specific sub-categories like 'Socket AM5 Motherboards'.
Extract complex shipping matrices calculating delivery costs to specific European postal codes.
Run continuous pipelines with hash-based change detection, delivering only pricing updates instead of full dumps.
Brief in. Clean data out.
Provide Geizhals category URLs, EAN lists, or specific merchant IDs. We map the target schema.
We configure Scrapy crawlers, European residential proxies, and Cloudflare bypass mechanisms.
Schema validation, null-rate checks, and price-outlier detection before full production launch.
JSON / CSV / Parquet pushed to your S3 bucket or Snowflake stage on your defined cadence.
Extracting from Geizhals requires navigating aggressive bot protection and deeply nested HTML structures. Here is our approach.
Geizhals employs strict rate limiting and Cloudflare protection. We utilize DACH-region residential proxies to maintain high concurrency without triggering CAPTCHAs or IP bans.
Hardware specifications on Geizhals are deeply nested. We parse these HTML tables into structured key-value JSON, normalising units and attributes across different manufacturers.
Shipping costs vary by destination country. We maintain localized sessions to extract accurate delivery matrices for AT, DE, and EU regions simultaneously.
Popular products feature hundreds of merchant offers. Our crawlers traverse deep pagination layers, capturing every tail-end merchant and obscure shipping configuration.
For daily price monitoring, we hash product records and emit only changed values. This reduces downstream ingestion costs for high-frequency repricing workflows.
Retailers track competitor pricing across the DACH region to adjust their own Geizhals listings and maintain top-3 visibility.
Component manufacturers analyze specification trends and pricing tiers to position new product launches effectively.
Marketplaces and distributors monitor merchant ratings and fulfillment performance across the Geizhals ecosystem.
eCommerce platforms ingest our webhooks to trigger automated repricing algorithms based on real-time market shifts.
Retailers extract Geizhals' highly accurate EANs, MPNs, and technical specifications to enrich their own product databases.
Identify price discrepancies between German, Austrian, and Polish retailers to optimize procurement and supply chain routing.
"Geizhals possesses the most rigorous hardware specification and cross-border pricing dataset in Europe. Accessing it programmatically requires specialized infrastructure."
Extracting Geizhals data at scale means navigating aggressive Cloudflare bot protection, complex session-based shipping calculations, and deeply nested HTML tables. DataFlirt manages the proxy rotation, parsing logic, and schema maintenance, delivering structured intelligence directly to your warehouse.
Everything supported by our geizhals.at 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 and Playwright orchestrated across Kubernetes clusters, handling dynamic shipping calculations and Cloudflare challenges.
Localized residential IPs from Germany and Austria ensure accurate regional pricing and bypass geo-fenced rate limits.
Custom Python 3.12 parsers convert complex Geizhals specification tables into strictly typed, queryable JSON schemas.
Data delivered to where your team already works — no new tooling required.
About geizhals.at scraping, legality, and pipeline operations.
Ask us directly →Scraping public pricing and specification data is generally permissible under EU law, provided it does not extract personal data or breach terms of service via authenticated sessions. DataFlirt targets strictly public, unauthenticated listings.
We utilize advanced TLS fingerprinting, automated Cloudflare challenge solvers (CapSolver), and DACH-region residential proxies to ensure uninterrupted data extraction.
Yes. Our pipelines support Geizhals' sister sites, allowing you to extract pricing and specs from the UK (Skinflint) and Poland (Cenowarka) using the same unified schema.
Yes. We configure crawler sessions with specific target countries (e.g., shipping to Austria vs. Germany) to extract accurate, localized shipping matrices from merchant offers.
Our parsers map Geizhals' deeply nested HTML specification tables into standardized JSON key-value pairs, normalising metrics like clock speeds, socket types, and dimensions.
For targeted EAN lists, we can configure high-frequency pipelines delivering updates every few hours via Webhook or S3 delta files, ideal for dynamic repricing algorithms.
Yes. We extract the data points powering Geizhals' historical price charts, providing a time-series view of lowest prices across the DACH region.
20-minute scoping call. Pilot dataset within the week. Production within two. From targeted EAN monitoring to full category specification dumps — we build and operate the pipeline. Define your scope today.
