We extract property listings, transaction histories, Redfin Estimates, and MLS metadata. 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 redfin.com. All fields typed and schema-versioned.
"property_id": "12345678", "address": "1428 Elm St", "city": "Seattle", "state": "WA", "price": 850000, "beds": 4, "baths": 3, "sqft": 2400
| # | property_id | address | city | state | zip_code | price |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Transaction History objects from redfin.com. All fields typed and schema-versioned.
"property_id": "12345678", "event_date": "2023-10-15", "event_type": "Sold", "price": 850000, "source": "NWMLS", "mls_id": "1849201"
| # | property_id | event_date | event_type | price | appreciation_pct | source |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Neighborhood Data objects from redfin.com. All fields typed and schema-versioned.
"walk_score": 85, "transit_score": 72, "bike_score": 90, "top_school_rating": 9, "flood_factor": 1, "neighborhood_name": "Capitol Hill"
| # | property_id | walk_score | transit_score | bike_score | school_district | top_school_name |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Financials & Taxes objects from redfin.com. All fields typed and schema-versioned.
"property_tax": 6240, "tax_year": 2023, "tax_assessment": 790000, "hoa_dues": 0, "price_per_sqft": 354, "rent_estimate": 4200
| # | property_id | property_tax | tax_year | tax_assessment | hoa_dues | price_per_sqft |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Agent Data objects from redfin.com. All fields typed and schema-versioned.
"agent_id": "98765", "agent_name": "Sarah Jenkins", "brokerage": "Redfin", "total_sales": 142, "active_listings": 6, "average_rating": 4.9
| # | agent_id | agent_name | brokerage | phone | total_sales | |
|---|---|---|---|---|---|---|
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Our infrastructure extracts property details, transaction histories, valuation models, and MLS metadata while circumventing advanced anti-bot protections.
Extract address, specifications, property type, year built, and lot dimensions directly from the listing page.
Capture the proprietary Redfin Estimate AVM for properties to track valuation changes over time.
Parse historical events including list price updates, pending statuses, and final sold prices with dates.
Extract Walk Score, Transit Score, and Bike Score metrics alongside top school ratings and flood factors.
Capture HOA dues, property tax history, tax assessments, and estimated mortgage variables.
Extract listing agent details, total sales volume, active listings, and client review ratings.
Input latitude and longitude coordinates to scrape all properties within a specific geographic polygon.
Extract high-resolution image URLs for property photos, floor plans, and virtual tour links.
Maintain a hash index of properties and only emit records when price, status, or estimate changes occur.
Brief in. Clean data out.
Provide zip codes, bounding box coordinates, or specific MLS regions. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, proxy rotation, and session management for redfin.com.
Schema validation, null-rate checks, and coordinate boundary verification before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Redfin uses aggressive fingerprinting and rate limits. We manage the infrastructure so you receive clean data.
Redfin employs strict bot detection heuristics. Our crawlers use US residential proxies with realistic browser fingerprints and full cookie session management to maintain high success rates.
Redfin property searches rely heavily on dynamic map rendering. We run full Playwright browser sessions to trigger map events and load properties hidden behind JavaScript pagination.
Much of Redfin's rich data is populated via internal GraphQL requests. We intercept these network calls directly to extract structured JSON before it hits the DOM.
Data structures vary depending on the regional MLS source. Our selectors normalise these variations into a consistent schema, ensuring your downstream pipelines do not break.
For continuous monitoring, we hash property states and only emit records when a status, price, or Redfin Estimate changes, reducing your storage and compute overhead.
Machine learning teams train automated valuation models using Redfin Estimates, property specs, and final sold prices.
Real estate investors identify undervalued properties by tracking days on market, price drops, and historical appreciation.
Analysts track median price trends, inventory levels, and transaction volume by zip code or neighbourhood.
Proptech platforms populate their databases with normalised MLS metadata, tax histories, and school ratings.
Brokerages identify high-volume selling agents and top performers in specific regions for targeted recruitment.
Lenders target newly listed properties or recent price drops to offer competitive financing products.
"Redfin aggregates the most accurate MLS data and proprietary valuation models on the market, but extracting it requires bypassing aggressive bot mitigation."
Property data is highly fragmented across regional MLS databases. Redfin normalises this catalogue, making it the ideal target for real estate analytics. DataFlirt manages the residential proxies, JavaScript rendering, and schema normalisation required to extract this data reliably at high volume.
Everything supported by our redfin.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 orchestration and deduplication. Playwright handles map rendering, cookie sessions, and GraphQL interception.
We maintain pools of US residential ISP proxies to circumvent Redfin bot protection. Rotation happens per-request with sticky sessions.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling, bounding box chunking, and SLA alerting.
Data delivered to where your team already works — no new tooling required.
About redfin.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available property data is generally permissible. DataFlirt extracts only public, non-authenticated listing, pricing, and MLS metadata. We do not circumvent authentication walls to access private user data. Clients should review Redfin ToS and consult legal counsel for specific use cases.
We use US residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. We monitor for 403 blocks in real time and trigger pool rotation automatically.
Real-time streaming pipelines achieve sub-60-minute latency for new listings and price drops within defined coordinate boundaries. Full region refreshes at daily cadence complete within an 8-hour window.
Yes. We accept latitude and longitude coordinate pairs to define custom geographic polygons, allowing precise extraction of specific neighbourhoods or development zones.
We extract the current Redfin Estimate visible on the listing. To build a historical time-series of estimates, we run continuous pipelines that snapshot the value at regular intervals.
Our smallest packages start at a defined region or list of zip codes with weekly delivery. For national coverage or real-time event streaming, we price based on compute volume and frequency.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off zip code dump or a continuous national property feed. We scope, build, and operate the pipeline.
