We extract residential and commercial listings, price trends, agent profiles, and DLD transaction histories from Bayut. 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 bayut.com. All fields typed and schema-versioned.
"id": "BAY-847291", "title": "Luxury 3 Bed Apartment with Marina View", "location": "Dubai Marina, Dubai", "price": 3200000.0, "bedrooms": 3, "size_sqft": 1850.5, "trucheck_status": true
| # | id | title | location | property_type | price | currency |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Agent Profiles objects from bayut.com. All fields typed and schema-versioned.
"name": "Sarah Jenkins", "agency": "Betterhomes", "languages": "['English', 'Arabic']", "active_listings_sale": 14, "phone_number": "+971501234567", "license_number": "BRN-49210"
| # | agent_id | name | agency | languages | nationality | experience_years |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Agency Data objects from bayut.com. All fields typed and schema-versioned.
"name": "Allsopp & Allsopp", "agents_count": 245, "orn_number": "1815", "total_properties": 1204, "contact_phone": "+97144294444", "website": "https://www.allsoppandallsopp.com"
| # | agency_id | name | location | total_properties | agents_count | trade_license |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Building Reviews objects from bayut.com. All fields typed and schema-versioned.
"location_name": "Princess Tower", "rating": 4.2, "review_text": "Great views but the elevators can be slow during peak hours.", "pros": "['Location', 'Views', 'Amenities']", "cons": "['Elevator wait times', 'Parking space']", "date_posted": "2026-02-14"
| # | review_id | location_name | reviewer_name | rating | review_text | date_posted |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Transaction History objects from bayut.com. All fields typed and schema-versioned.
"property_name": "Unit 1402", "transaction_type": "Sale", "price": 1450000.0, "date": "2026-04-10", "price_per_sqft": 1250.0, "usage_type": "Residential"
| # | transaction_id | property_name | location | transaction_type | price | date |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Our Bayut scraper handles every layer of the platform: property listings, dynamic pricing, agent intelligence, and DLD transaction data - with JavaScript rendering, session management, and anti-bot circumvention built in.
Title, description, price, size, bedrooms, bathrooms, amenities, and location metadata - scraped at the individual listing level.
Extract agent names, broker registration numbers (BRN), active listing counts, languages spoken, and agency ORN details.
Capture the TruCheck badge status and validation timestamps to filter out fake or outdated property listings.
Extract historical Dubai Land Department sale and rent transactions associated with specific buildings or communities.
Monitor asking prices for rent and sale listings, capturing drops and increases timestamped per crawl.
Extract exact map coordinates and community polygon data to feed directly into your GIS or mapping systems.
Execute JavaScript to simulate user clicks, revealing hidden agent phone numbers and WhatsApp contact links.
Extract structured lists of building amenities and direct URLs to 2D and 3D floor plan images.
Run one-off bulk exports or configure continuous pipelines at daily or weekly cadences with change-detection diffing.
Brief in. Clean data out.
Provide target communities, property types, or agent lists. We design the extraction schema together.
We configure Scrapy / Playwright crawlers, proxy rotation, session management, and CAPTCHA handling for bayut.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.
Bayut uses strict rate limits and bot protection to guard its property data. Here is how we stay resilient - and why teams choose managed infrastructure over DIY.
Bayut employs strict rate limiting and bot detection via Cloudflare. Our crawlers use residential ISP proxies with realistic browser fingerprints, randomised request timing, and full cookie session management - trained on real user behaviour patterns.
Critical data points like agent phone numbers and WhatsApp links require user interaction to render. We run full Playwright browser sessions to trigger these JavaScript events and capture the revealed data.
Bayut caps search result pagination, hiding thousands of listings in broad searches. We programmatically slice search queries by micro-locations, property types, and tight price brackets to ensure 100% market coverage.
For tracking price drops across the UAE, we maintain a hash index of last-seen values per listing. Subsequent runs only push diffs - reducing compute cost and downstream processing load.
Every run emits structured logs to our observability stack. We alert on null-rate spikes, missing TruCheck fields, schema drift, and coverage drops - and respond before you notice.
Firms feed asking prices, transaction histories, and location data into AVMs (Automated Valuation Models) to price assets accurately.
Investors correlate sale prices with rental asking rates in specific towers to identify high-yield investment opportunities.
Brokerages monitor competitor agents, tracking their active listing volume, TruCheck ratios, and time-on-market metrics.
Real estate agencies track market share by scraping which brokerages hold the most exclusive listings in prime Dubai neighbourhoods.
Analysts track inventory levels, price-per-square-foot trends, and days-on-market to forecast macro real estate cycles.
Startups use structured Bayut listing and amenity data to bootstrap their own property management or tenant-matching platforms.
"Bayut holds the definitive dataset for UAE real estate - but extracting complete market coverage requires bypassing complex rate limits and JavaScript rendering."
Most teams underestimate the investment required: reliable Bayut scraping requires residential proxies, full JavaScript execution to reveal contact details, 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 bayut.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, cookie sessions, and interaction flows. Combined via scrapy-playwright middleware.
We maintain pools of residential ISP proxies across AE/US/UK regions. Rotation happens per-request with sticky sessions where required. IP score monitoring prevents blacklisted pool contamination.
Pipelines run on AWS Lambda (burst) and ECS (sustained). 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 bayut.com scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information from Bayut is generally permissible under applicable law - reinforced by standard web scraping precedents. DataFlirt targets only public, non-authenticated property, pricing, and agent data. We do not extract personal data beyond public business contacts, circumvent authentication walls, or violate GDPR/PDPL. Clients should review Bayut's ToS and consult legal counsel for specific use cases.
Bayut masks phone numbers and WhatsApp links behind a 'Call' or 'Email' button to prevent simple HTML parsing. We use Playwright to load the page, execute the necessary JavaScript, simulate a user click, and extract the revealed contact string.
Yes. Every pipeline run produces timestamped snapshots. We maintain a time-series record per listing ID, allowing you to track original asking price, current price, and the exact date of any reductions.
Full catalogue refreshes for specific emirates (like Dubai or Abu Dhabi) typically complete within a 12-24 hour window depending on scale. Targeted pipelines tracking specific buildings or communities can run at hourly intervals.
Yes. We extract the historical transaction records published by the Dubai Land Department that Bayut displays on building and community pages, including sale price, date, and price per square foot.
Our smallest packages start at a defined location list or specific property type with weekly delivery. For full UAE market coverage or custom schema requirements, we price based on volume and delivery frequency. Contact us with your use case for a scoped quote.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a one-off property dump or a continuous price monitoring feed across the UAE - we scope, build, and operate the pipeline. Tell us what you need.
