We extract vintage furniture listings, art provenance, dealer profiles, and pricing signals from 1Stdibs. 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 Listings objects from 1stdibs.com. All fields typed and schema-versioned.
"item_id": "F-129485", "title": "Mid-Century Modern Walnut Credenza", "creator": "George Nelson", "period": "1950s", "price": 8500.0, "currency": "USD", "condition": "Excellent - Minor wear consistent with age and history"
| # | item_id | title | creator | period | materials | dimensions |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Dealer Intelligence objects from 1stdibs.com. All fields typed and schema-versioned.
"dealer_id": "D-9382", "dealer_name": "Galerie Moderne", "location_city": "Paris", "location_country": "France", "member_since": "2014", "active_listings_count": 142, "response_time": "Within 24 hours"
| # | dealer_id | dealer_name | storefront_url | location_city | location_country | rating |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Art & Provenance objects from 1stdibs.com. All fields typed and schema-versioned.
"artist": "Pablo Picasso", "medium": "Lithograph on paper", "signature": "Hand-signed lower right", "creation_year": 1962, "authentication_status": "Certificate of Authenticity included", "frame_dimensions": "24 x 36 in"
| # | item_id | title | artist | medium | signature | creation_year |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Pricing & Offers objects from 1stdibs.com. All fields typed and schema-versioned.
"item_id": "F-129485", "listed_price": 8500.0, "make_offer_available": true, "ships_from": "New York, NY", "shipping_cost": 450.0, "price_timestamp": "2023-10-24T08:12:00Z", "currency": "USD"
| # | item_id | listed_price | currency | shipping_cost | ships_from | make_offer_available |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Search & Taxonomy objects from 1stdibs.com. All fields typed and schema-versioned.
"keyword": "mid century credenza", "category_path": "Furniture > Storage > Credenzas", "style_filter": "Mid-Century Modern", "position": 3, "item_id": "F-129485", "scraped_at": "2023-10-24T08:14:22Z"
| # | keyword | category_path | style_filter | period_filter | position | item_id |
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Our 1Stdibs scraper handles every layer of the platform: dealer storefronts, vintage inventory, provenance metadata, and pricing signals. We bypass strict perimeter defences to deliver structured JSON.
Title, creator, dimensions, materials, period, and condition notes scraped across all furniture and art categories.
Storefront URLs, active inventory size, geographic location, and response times for every seller on the platform.
Extract signature details, certificates of authenticity, and historical provenance text for fine art listings.
Parse Next.js state data to extract uncompressed, high-resolution source URLs for imagery.
Capture listed price, currency, shipping estimates, and the availability of Make an Offer functionality.
Deep scrape of styles, periods, and makers to map the entire 1Stdibs classification system.
Origin cities, countries, and shipping cost estimates normalised across global dealer locations.
Handle geo-located pricing and availability based on specific target markets and currencies.
Run one-off bulk exports or configure continuous pipelines at daily cadences with change-detection diffing.
Handle Datadome and PerimeterX blocks using residential proxies and TLS fingerprinting.
Brief in. Clean data out.
Provide dealer URLs, category paths, creator names, or search keywords. We design the extraction schema together.
We configure Scrapy crawlers, proxy rotation, session management, and CAPTCHA handling for 1stdibs.com.
Schema validation, null-rate checks, and sample extraction before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Luxury marketplaces invest heavily in scraping detection. Here is how we stay resilient and why teams choose managed infrastructure over DIY.
1Stdibs uses strict Web Application Firewalls. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management trained on real user behaviour patterns.
The platform relies heavily on React and Next.js hydration. We run full Playwright browser sessions with JavaScript execution and lazy-load triggering to capture data that headless HTTP clients miss entirely.
DOM structures change frequently. Our selector strategy uses multiple fallback chains per field, including JSON state extraction, so a layout change does not break your data pipeline overnight.
Instead of scraping compressed viewport images, we parse the underlying JSON application state to extract the original, uncompressed image URLs for art and furniture listings.
For large dealer catalogues, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs, reducing compute cost and downstream processing load.
Appraisers and auction houses track vintage market values and pricing floors for specific creators and periods.
High-end dealers monitor rival inventory, pricing strategies, and active listing counts.
Design firms aggregate specific styles, materials, and periods for large commercial or residential projects.
Machine learning teams train visual recognition models on verified period furniture and fine art imagery.
Analysts identify rising demand and inventory scarcity for specific designers or mid-century eras.
Funds and analysts track liquidity and price stability for blue-chip fine art and collectible design.
"1Stdibs holds the definitive digital record of vintage furniture and fine art pricing, but querying market value requires bypassing strict perimeter defences."
Most teams underestimate the investment required: reliable 1Stdibs scraping requires residential proxies, full JavaScript rendering for Next.js hydration, CAPTCHA handling, and daily selector maintenance. DataFlirt absorbs that complexity so your engineers can focus on the analysis, not the infrastructure.
Everything supported by our 1stdibs.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 interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies. Rotation happens per-request with sticky sessions 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 stored in managed Postgres.
Data delivered to where your team already works — no new tooling required.
About 1stdibs.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from 1Stdibs is generally permissible under applicable law, reinforced by the hiQ v. LinkedIn ruling. DataFlirt targets only public, non-authenticated listing, dealer, and pricing data. We do not extract personal buyer data or circumvent authentication walls.
We use residential ISP proxies, full Playwright browser sessions with realistic TLS fingerprints, and request timing modelled on human behaviour. We monitor for WAF blocks in real time and trigger pool rotation automatically.
Yes. We bypass the compressed viewport images loaded in the browser and extract the uncompressed, high-resolution asset URLs directly from the application state data.
Yes. We capture whether a listing accepts offers alongside the stated list price, providing deeper signals on pricing flexibility.
Full catalogue refreshes at daily cadence complete within a 6 to 12 hour window depending on category size. Targeted dealer inventory can be scraped at hourly intervals.
Yes. Pipelines can be scoped to specific designers, art movements, material types, or geographic dealer locations based on your requirements.
Our smallest packages start at a defined category or dealer list with weekly delivery. For full platform extraction, we price based on compute volume and delivery frequency.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off catalogue dump or a continuous price-monitoring feed across dealer inventories, we scope, build, and operate the pipeline. Tell us what you need.
