Real Estate Data Tools — US, UK, EU, APAC Property Scrapers

Q: Can I track price changes over time?

Yes. The Redfin and Zillow actors already extract priceHistory arrays from each listing page (every reduction, withdrawal, relist, and sale, with timestamps and dollar amounts). For the others, schedule the actor daily, append outputs to a table partitioned by run date, and you have your own time-series. Most teams diff price by listing_id across runs to detect drops the same day they happen.

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Property data is one of the highest-friction verticals on the open web. Listings sit behind aggressive bot defences, fragmented MLS rules, country-specific portals, government registries that publish PDFs instead of APIs, and incumbent data vendors charging four-figure monthly subscriptions for what is fundamentally publicly visible information. This category page collects every real estate scraper and property data tool we maintain, covering residential listings, commercial inventory, rental markets, historic transactions, and government registry feeds across the US, UK, Hong Kong, Singapore, and Denmark — with active development underway for Sweden, the Netherlands, India, and additional APAC markets.

Who actually uses this data? REIT analysts modelling rental yield by submarket and rebalancing portfolios off live cap-rate drift. PropTech founders building inventory feeds, valuation engines, and lead-scoring products without paying for MLS access. Buy-to-let investors comparing London boroughs against Hong Kong districts before deploying capital across jurisdictions. Brokers stitching together cross-border portfolios for HNW clients who want one dashboard, not seven portal logins. Market researchers tracking gentrification, foreign-buyer flows, and price-per-square-foot drift across decades of registry data. Journalists exposing investor concentration in starter-home markets and the corporate landlord build-up. Wholesalers running automated comp packets to flip distressed inventory in 24 hours instead of three days.

Every actor listed below is a ready-made Apify scraper — point it at a search URL or a market boundary, get structured JSON or CSV out the other side, run it on a schedule, no headless browser babysitting required. Pricing is per-event or per-compute-unit, typically fractions of a cent per listing. Free Apify tier ($5/month of compute) is enough to evaluate any actor against your real workflow before you commit a dollar.

Common use cases

Track Bay Area listing inventory daily and alert on new sub-$1.2M listings in target zip codes
Monitor London rental yields by postcode for buy-to-let analysis and refinancing decisions
Build a Hong Kong property price index alternative to Centaline using Land Registry transaction records
Aggregate Singapore HDB resale prices with private-market transactions for a combined market view
Run weekly Redfin vs Zillow price-difference reports to surface mispriced inventory before it moves
Power a PropTech valuation model with historical comps pulled directly from listing portals
Build a Denmark-wide market dashboard from Boliga listing data for Nordic real estate funds
Generate broker comp packets in minutes instead of hours by automating listing pull + photo download

Featured tools

United States

Tool	Source	Region	Key fields	Best for
Redfin Scraper	Redfin.com	US	Price, beds/baths, sqft, lot size, price history, days on market, comps, photos, school ratings	Investment analysis, wholesaler deal flow, comp packets
Zillow Scraper	Zillow.com	US	Zestimate, rent estimate, tax history, ownership records, agent details, neighborhood stats	Zestimate tracking, rental yield models, agent prospecting

United Kingdom

Tool	Source	Region	Key fields	Best for
Rightmove UK Scraper	Rightmove.co.uk	UK	Asking price, postcode, property type, rooms, EPC rating, agent, listing date, sold history	Buy-to-let yield analysis, London borough comps, agent share-of-listings

Hong Kong

Tool	Source	Region	Key fields	Best for
HK Land Registry — Transactions	landreg.gov.hk	HK	Transaction date, consideration, address, estate, area, vendor/purchaser type, instrument number	Building a Centaline-alternative price index, foreign-buyer studies, gov-grade audit trail

Singapore

Tool	Source	Region	Key fields	Best for
Singapore HDB Resale Price Tracker	data.gov.sg	SG	Block, town, flat type, lease commence, floor area, resale price, transaction month	HDB cash-over-valuation tracking, town-level price trends, lease-decay modelling

Northern Europe

Tool	Source	Region	Key fields	Best for
Boliga Denmark Real Estate	Boliga.dk	DK	Asking price, sold price, m², rooms, build year, energy class, days on market, postnummer	Nordic market dashboards, Copenhagen vs Aarhus comps, energy-rating premium analysis

Coverage in active development (currently private actors): HK Centaline Property Index (CCL tracker), Singapore URA Private Property Transactions, Singapore URA Commercial Property (office, retail, industrial), Singapore Rental Market Tracker (HDB + private rentals), India MagicBricks. The Sweden Hemnet, Netherlands Funda, and UK Zoopla actors are being rebuilt after source-site changes broke the previous versions — sign up for the newsletter for release notifications. Reach out via the contact form if you need API access to private actors ahead of public release; we routinely white-label them for funds and proptech teams that need exclusive feeds.

How to choose between actors in the same market

In the US, Redfin is the better source if you care about clean comps, days-on-market, and Redfin’s own valuation estimate — its rendering is more structured and its valuation methodology is transparent. Zillow is the better source if you care about Zestimates, rental estimates, ownership records, and broader inventory — Zillow indexes a wider set of off-MLS and FSBO listings. Many teams run both and reconcile. In the UK, Rightmove dominates listing share (~80%), so it’s the default; Zoopla coverage (when our actor relaunches) complements rather than replaces it. In Singapore, HDB Resale Tracker covers ~75% of all residential transactions by volume because the HDB sector is that large — for the private-market piece you’ll want URA. In Hong Kong, the Land Registry is the authoritative source of record; Centaline’s CCL is a useful derived index but is downstream of the same registry data.

Workflow example: daily multi-market REIT inventory tracker

Here’s how a small REIT analytics team uses three of these actors together to feed a normalized cross-market dashboard:

06:00 UTC — pull US inventory. Schedule the Redfin scraper against a saved San Francisco search URL filtered to 2-4 bedroom SFR under $2M. Output: ~400 listings with price, sqft, price history, days on market, and Redfin’s own valuation estimate.
06:15 UTC — pull UK inventory. Schedule Rightmove against a saved Zone 1-3 London search URL filtered to flats under £750k. Output: ~600 listings with asking price, postcode, EPC rating, and agent.
06:30 UTC — pull HK transactions. Schedule HK Land Registry for the prior trading day’s registered transactions. Output: ~80-150 records with consideration in HKD, estate, area, vendor/purchaser classification.
07:00 UTC — normalize to common schema. A small Python script in a GitHub Actions job converts all three feeds to a unified {market, listing_id, asof, address, price_local, price_usd, ppsqft_usd, listing_type, source_url} CSV. FX conversion uses our real-time FX feed.
07:05 UTC — append to BigQuery + push to dashboard. A single bq load command appends today’s CSV to a partitioned table. Looker Studio refreshes against the new partition and re-renders the multi-market inventory chart, median ppsqft trend, and new-listing alerts panel.

Total monthly Apify cost for this pipeline at ~30k records/day: under $40. Replacing the equivalent paid feeds (MLS subscriptions + UK Land Registry vendor + HK property data terminal) costs north of $2,000/month, and most paid feeds still don’t give you the cross-market normalization step — they hand you three incompatible schemas and a contract that forbids redistribution. Owning your own pipeline means you control the schema, the cadence, the retention policy, and the cost.

Variations on this same pattern work for residential wholesalers (Redfin only, daily, alert on price drops > 5%), Singapore-focused property funds (HDB Resale + a future URA private actor, weekly aggregation), and Nordic family offices (Boliga across Denmark, with planned Hemnet/Sweden integration once we re-publish that actor). The infrastructure is the same — only the actor mix and the schedule change.

Related categories

SEC Filings Toolkit — 13F, Form 4, 8-K and 13D feeds for institutional capital tracking
Singapore Data Stack — ACRA, HDB, URA, MAS and SGX as one toolkit
Hong Kong Data Toolkit — HKEX, Centaline, Land Registry and corporate registry feeds
Global Markets Toolkit — LSE, Xetra, TSX, ASX, B3 and more
VC Sourcing Toolkit — pre-seed pipeline faster than Crunchbase
Shopify Toolkit — catalog, revenue, pricing intel for 4.4M stores
B2B Lead-Gen Stack — Apollo & ZoomInfo alternative for SDR teams

Frequently asked questions

How fresh are the listings?

It depends on how you schedule the actor. Run-on-demand returns the live state of the source site at request time — typically within seconds of what a human visitor would see. On a schedule (hourly, daily, weekly), each run pulls fresh data; the previous run’s output stays in your dataset history so you can compute deltas. For high-velocity markets like SF or central London, a daily 06:00 pull catches most overnight changes; for slower markets, weekly is plenty. Government registry sources (HK Land Registry, Singapore HDB) publish on their own cadence — typically T+1 to T+5 business days after the transaction registers — so daily polling is the practical ceiling there regardless of how often you run the actor.

Can I track price changes over time?

Yes. The Redfin and Zillow actors already extract priceHistory arrays from each listing page (every reduction, withdrawal, relist, and sale, with timestamps and dollar amounts). For the others, you do it by accumulation: schedule the actor daily, append outputs to a table partitioned by run date, and you have your own time-series. Most teams diff price by listing_id across runs to detect drops the same day they happen — that’s the single most actionable signal for wholesalers and value-add buyers. For longer-horizon analysis (12+ month price drift, seasonal patterns), you want monthly aggregation grouped by zip/postcode/town to smooth out single-listing noise.

What about MLS access?

None of these actors touch MLS. They scrape public-facing portal pages — the same pages a buyer or browser would see. That keeps you on the right side of MLS licensing rules (which forbid bulk redistribution) while still giving you 90% of the field coverage. If you need full MLS feeds (every off-market listing, agent-only fields, exact GPS), you need a paid MLS license. If you need the public market state — what buyers can actually see and act on — these actors are sufficient.

How do you handle Cloudflare and anti-bot on these sites?

All actors run on Apify’s residential proxy infrastructure with automatic session rotation, browser fingerprint randomization, and stealth headers. Where a site uses progressive challenges (Rightmove, Zillow), the actor falls back to a real browser (Playwright/Chromium) and solves the JS challenge naturally. You do not configure any of this — it’s handled inside the actor. Sites that have actively broken (Apartments.com as of mid-2026) are flagged as deprecated and removed from this page rather than left as silent failures.

What about commercial property coverage?

Public commercial coverage on this page is currently limited to HK Land Registry (which records commercial transactions alongside residential) and the Boliga/Rightmove commercial subsets. Our Singapore URA Commercial actor (office, retail, industrial transactions and rents) is currently a private actor — contact us for API access. For US commercial, the Redfin/Zillow actors include some commercial-zoned listings but coverage is patchy versus dedicated providers like CoStar.

What does it cost per listing?

Apify’s pricing model is per-event (PPE) or per-compute-unit. For most of these actors, you’re looking at fractions of a cent per listing once you factor in compute and proxy. A 1,000-listing daily pull from Redfin runs ~$1-2. A 10,000-listing weekly pull from Rightmove runs ~$8-15. HK Land Registry and Singapore HDB are even cheaper because they hit structured government datasets rather than scrape rendered HTML. Free tier on Apify includes $5/month of compute — enough to evaluate any actor against your real workflow before committing. Compare that to MLS access (typically $500-2,000/month per market plus broker affiliation requirements) or commercial data terminals (CoStar starts at $1,500/month and scales fast) and the economics for sub-enterprise workloads are not close.

Get started

Pick the market you care about most, click through to the actor on Apify, and run a test against one of your saved search URLs. Free Apify tier handles the first few hundred listings; from there, schedule it daily and start building your own time-series. For multi-market dashboards or custom field extraction, get in touch.

Browse the full NexGenData actor library on Apify — 300+ scrapers across real estate, financial markets, government registries, and more.