We extract HDB resale flats, private condos, landed properties, agent directories, and rental data from PropertyGuru. 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 Sale Listings objects from propertyguru.com.sg. All fields typed and schema-versioned.
"listing_id": "24918341", "title": "Marina Bay Residences", "price_sgd": 3200000, "price_psf": 2854, "district": "D01 Boat Quay / Raffles Place", "property_type": "Condominium", "beds": 3, "area_sqft": 1121, "tenure": "99-year Leasehold"
| # | listing_id | title | price_sgd | price_psf | district | address |
|---|---|---|---|---|---|---|
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Complete list of extractable fields for Rental Listings objects from propertyguru.com.sg. All fields typed and schema-versioned.
"listing_id": "23948112", "title": "The Sail @ Marina Bay", "monthly_rent_sgd": 6500, "furnishing": "Fully Furnished", "beds": 2, "baths": 2, "area_sqft": 883, "availability_date": "2026-08-01", "district": "D01 Boat Quay / Raffles Place"
| # | listing_id | title | monthly_rent_sgd | deposit_sgd | availability_date | furnishing |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Agent Profiles objects from propertyguru.com.sg. All fields typed and schema-versioned.
"agent_id": "84719", "name": "Jane Doe", "agency_name": "PropNex Realty Pte Ltd", "cea_reg_no": "R123456A", "phone_number": "+65 9123 4567", "active_sale_listings": 42, "active_rent_listings": 18, "rating": 4.9, "review_count": 128
| # | agent_id | name | agency_name | cea_reg_no | phone_number | active_sale_listings |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Condo Projects objects from propertyguru.com.sg. All fields typed and schema-versioned.
"project_id": "P3921", "name": "Reflections at Keppel Bay", "district": "D04 Harbourfront / Telok Blangah", "developer": "Keppel Bay Pte Ltd", "top_year": 2011, "total_units": 1129, "tenure": "99-year Leasehold", "avg_psf": 1950
| # | project_id | name | district | developer | top_year | total_units |
|---|---|---|---|---|---|---|
| 1 | ||||||
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Complete list of extractable fields for Transaction History objects from propertyguru.com.sg. All fields typed and schema-versioned.
"transaction_id": "T918237", "project_name": "Pinnacle @ Duxton", "block_number": "1G", "floor_level": "41-45", "area_sqft": 1141, "price_sgd": 1350000, "price_psf": 1183, "date_sold": "2026-01-15"
| # | transaction_id | project_name | block_number | floor_level | area_sqft | price_sgd |
|---|---|---|---|---|---|---|
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Our PropertyGuru scraper extracts every layer of the residential and commercial market: HDB resale flats, private condos, landed properties, and agent directories.
Extract comprehensive details for public and private housing, including block numbers, floor levels, lease balances, and TOP dates.
Capture asking prices, historical transaction prices, and per-square-foot metrics to track district-level valuation changes.
Extract agent names, phone numbers, agency affiliations, and CEA registration numbers across the entire broker directory.
Capture proximity to MRT stations, primary schools, supermarkets, and expressways for every listing.
Extract high-resolution image URLs, virtual tour links, and floor plan images associated with listings and new launches.
Scrape URA-matched transaction data displayed on property pages to build accurate valuation models.
Extract data for offices, retail spaces, shophouses, and industrial properties with commercial-specific zoning fields.
Support for PropertyGuru Malaysia and other regional domains using the same normalised data schema.
Run daily or weekly pipelines that only output new listings, price drops, or status changes, saving processing time.
Brief in. Clean data out.
Provide target districts, property types, or agent lists. We design the extraction schema together.
We configure Scrapy and Playwright crawlers, handle Cloudflare Turnstile, and manage request limits for propertyguru.com.sg.
Schema validation, null-rate checks, and data normalisation before full launch.
JSON, CSV, or Parquet pushed to your S3 bucket, BigQuery dataset, or Snowflake stage on agreed cadence.
PropertyGuru protects its listing database with Cloudflare and aggressive rate limiting. Here is how our infrastructure maintains continuous extraction.
PropertyGuru uses Cloudflare to block automated traffic. We use Playwright with stealth plugins, realistic TLS fingerprints, and CAPTCHA solvers to bypass Turnstile challenges without triggering blocks.
Proximity data and map pins load dynamically via API calls after the initial page render. Our crawlers intercept these XHR responses directly to extract precise geo-coordinates and POI distances.
Agent phone numbers require a click to reveal, triggering an API call that is strictly rate-limited per IP. We distribute these requests across a large pool of Singapore residential proxies to extract contact details at scale.
Search results are capped at 50 pages. We use algorithmic search splitting, generating granular queries by district, price bracket, and property type to ensure 100% coverage of the active listing inventory.
Public and private properties have different metadata structures. We normalise these into a unified schema, ensuring that leasehold durations, block numbers, and developer details align perfectly in your database.
Automated valuation models (AVMs) ingest asking prices and transaction history to generate instant property estimates.
Real estate agencies track competitor listings, agent performance, and market share across different districts.
Institutional investors correlate rental asking prices with sale prices to calculate gross rental yields by project.
Banks and brokers monitor new listings and TOP dates to target buyers and sellers with financing products.
Researchers analyse property density, price heatmaps, and MRT proximity to inform infrastructure development.
Relocation firms aggregate rental availability and pricing to advise corporate clients on housing budgets.
"PropertyGuru holds the definitive dataset for Singapore real estate, but turning web pages into queryable market intelligence requires resilient infrastructure."
Extracting data at scale from PropertyGuru means solving Cloudflare Turnstile, handling dynamic map hydration, and managing rate limits on phone number reveals. We build and maintain the extraction layer so your analysts can focus on yield modelling and valuation algorithms rather than proxy rotation.
Everything supported by our propertyguru.com.sg 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 deduplication. Playwright handles JavaScript rendering, Cloudflare challenges, and interaction flows like phone number reveals.
We maintain pools of residential ISP proxies localised to Singapore. Rotation happens per-request to avoid rate limits on API endpoints.
Pipelines run on AWS Lambda and ECS. Airflow handles scheduling and SLA alerting. All state is stored in managed PostgreSQL.
Data delivered to where your team already works — no new tooling required.
About propertyguru.com.sg scraping, legality, and pipeline operations.
Ask us directly →Scraping publicly available information is generally permissible. DataFlirt targets only public, non-authenticated real estate listings and agent profiles. We do not extract personal data beyond what agents publish for business contact. Clients should review PropertyGuru terms of service and consult legal counsel for specific use cases.
We use Playwright with stealth configurations, realistic browser fingerprints, and automated solvers to pass Turnstile challenges seamlessly without manual intervention.
Yes. The phone numbers require an interaction to reveal. Our crawlers simulate this interaction and capture the resulting API response, rotating IPs to respect rate limits.
We can configure pipelines to run daily, weekly, or continuously. For continuous pipelines, we track new listings and price changes, delivering updates within hours.
Yes. Public HDB flats and private condominiums have different data structures on the site. We map these into a unified schema so you can query across all property types easily.
Yes. PropertyGuru limits search results to 50 pages. We bypass this by generating highly granular search queries based on micro-districts and price brackets to extract the full inventory.
Yes. We provide a sample run of up to 1,000 listings as part of the pre-engagement scoping process so you can validate schema fit and data quality.
20-minute scoping call. Pilot dataset within the week. Production within two. Whether you need a daily sync of all HDB resale listings or a continuous feed of private condo transactions, we build and operate the pipeline. Tell us what you need.
