We extract apartment listings, pricing history, floor plan variants, amenity lists, and property management details from Rent.com. 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 rent.com. All fields typed and schema-versioned.
"property_id": "p_193847", "name": "The Avery", "city": "Austin", "state": "TX", "zip_code": "78702", "walk_score": 85, "property_type": "Apartment"
| # | property_id | url | name | address | city | state |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Floor Plans & Units objects from rent.com. All fields typed and schema-versioned.
"floor_plan_id": "fp_99281", "beds": 2, "baths": 2, "sqft_min": 1050, "price_min": 2450, "availability_status": "Available Now", "available_date": "2024-05-01"
| # | floor_plan_id | property_id | plan_name | beds | baths | sqft_min |
|---|---|---|---|---|---|---|
| 1 | ||||||
| 2 | ||||||
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Complete list of extractable fields for Pricing & Concessions objects from rent.com. All fields typed and schema-versioned.
"unit_number": "B-402", "current_price": 2450, "previous_price": 2500, "concession_text": "1 Month Free on 12 Month Lease", "deposit_amount": 500, "price_timestamp": "2023-10-24T08:14:00Z"
| # | property_id | floor_plan_id | unit_number | current_price | previous_price | price_timestamp |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Amenities & Policies objects from rent.com. All fields typed and schema-versioned.
"pet_policy_cats": true, "pet_policy_dogs": true, "pet_rent": 25, "pet_deposit": 250, "parking_type": "Covered Garage", "laundry_type": "In Unit"
| # | property_id | in_unit_amenities | community_amenities | pet_policy_cats | pet_policy_dogs | pet_rent |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Property Managers objects from rent.com. All fields typed and schema-versioned.
"management_company": "Greystar", "office_hours": "Mon-Fri 9AM-6PM", "contact_phone": "512-555-0198", "rating": 4.2, "review_count": 128, "response_time": "Within 24 hours"
| # | property_id | management_company | office_hours | contact_phone | contact_email | website_url |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Rent.com scraper handles every layer of the platform: property listings, dynamic pricing, floor plan variants, and pet policies - with JavaScript rendering and bot circumvention built in.
Beds, baths, square footage, coordinates, and year built - scraped at property level with parent-child floor plan mapping.
Extract unit-level details including specific availability dates, square footage ranges, and layout names.
Capture daily price fluctuations, concessions like '1 month free', and deposit fees - timestamped per crawl.
Extract deposit amounts, breed restrictions, monthly pet rent, and specific allowances for cats and dogs.
Split community amenities from in-unit features, normalising data for fitness centres, pools, and parking types.
Extract high-resolution image arrays, Matterport links, and video tour URLs for every property.
Capture Walk Scores, Transit Scores, and assigned school ratings associated with each listing.
Extract management company names, office hours, and contact phone numbers for every listing.
Scrape by zip code, city, or custom coordinate radius to ensure total coverage of metropolitan statistical areas.
Track price drops and availability changes over time with hash-based change detection.
Brief in. Clean data out.
Provide zip codes, cities, or property URLs. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for rent.com.
Schema validation, null-rate checks, price-outlier detection, and sample property records before full launch.
JSON / CSV / Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
Rent.com uses map-based pagination and heavy bot mitigation. Here is how we stay resilient - and why teams choose managed infrastructure over DIY.
Rent.com blocks automated traffic using advanced bot detection. Our crawlers use residential ISP proxies with realistic browser fingerprints and full cookie session management - trained on real user behaviour patterns.
Rent.com search results and property pages are heavily JavaScript-rendered. We run full Playwright browser sessions with JavaScript execution and lazy-load triggering - capturing data that headless HTTP clients miss entirely.
Property layouts vary wildly depending on the management company. Our selector strategy uses multiple fallback chains per field so a missing amenity list does not break your data pipeline overnight.
For large metropolitan areas, we maintain a hash index of last-seen values per field. Subsequent runs only push diffs - reducing compute cost and downstream processing load.
Standard list pagination often misses properties. We paginate using coordinate bounding boxes to ensure total coverage of a target market without hitting result limits.
Revenue management systems use market comps to adjust unit pricing dynamically based on local supply.
Acquisition teams track yield, cap rates, and market saturation across target zip codes.
Firms compare their concession strategies and pet policies against local competitors.
Analyse days-on-market and availability dates to gauge rental demand in emerging neighbourhoods.
Track housing affordability, concession trends, and inventory across major metropolitan statistical areas.
Aggregate listings based on strict pet policies, deposit requirements, and commute times for corporate clients.
"Rent.com holds the ground truth for multifamily housing supply and pricing, but extracting it requires navigating dynamic map grids and aggressive bot mitigation."
Scraping rental listings at scale is not a simple HTTP GET operation. Rent.com uses heavy JavaScript rendering for map-based search results and aggressive bot protection to block automated traffic. DataFlirt manages the residential proxies, browser fingerprinting, and layout variations so your data science team receives clean, normalised property records.
Everything supported by our rent.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, deduplication, and retry logic. Playwright handles JavaScript rendering, map interactions, and dynamic floor plans.
We maintain pools of residential ISP proxies across US regions. Rotation happens per-request with sticky sessions where required to bypass rate limits.
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 rent.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Rent.com is generally permissible under applicable law. DataFlirt targets only public, non-authenticated property and pricing data. We do not extract personal user data or circumvent authentication walls. Clients should review terms of service and consult legal counsel for specific use cases.
We use residential ISP proxies, full Playwright browser sessions with realistic fingerprints, and request timing modelled on human behaviour. We monitor for CAPTCHA rate spikes in real time and trigger solver queues automatically.
Yes. Every pipeline run produces timestamped snapshots. We maintain a time-series table per property and floor plan for price changes from the date your pipeline starts.
Yes, we extract unit-level details including square footage, beds, baths, prices, and specific availability dates mapped to the parent property.
We can run pipelines daily or hourly depending on your requirements. Real-time streaming pipelines achieve low latency for price signals on a defined zip code set.
Our smallest packages start at a defined zip code list or metropolitan statistical area with weekly delivery. For national coverage, we price based on volume and delivery frequency.
Yes, we capture breed restrictions, pet rent, and deposit amounts, categorised specifically for cats and dogs.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off export of a single MSA or continuous price-monitoring across the entire US - we scope, build, and operate the pipeline. Tell us what you need.
