Gulf used-car listings — search & export

It is structured, machine-readable records of pre-owned cars advertised for sale on UAE marketplaces. Each row captures fields such as make, model, year, trim, price in AED, mileage in kilometres, fuel type, transmission, body type, seller type (dealer or individual), GCC-spec flag, location, the listing URL and a scrape timestamp. Individual fields are populated when the source listing exposes them and may be empty otherwise. It turns scattered web ads into a clean dataset you can analyse, filter and join.

The query builder targets the major Gulf used-car marketplaces — DubiCars (a UAE dealer-focused portal with roughly 24,000 used cars listed in Dubai) and Dubizzle Motors (a consumer marketplace with over 34,000 used cars in Dubai). You choose one or more platforms in the platforms field. Results are normalized into one consistent schema so a DubiCars row and a Dubizzle row look the same.

No. This is a query builder. You assemble the configuration (platforms, make, model, per-platform cap) and preview a fixed example of the output shape so you know exactly what fields you will get. The source sites are anti-bot protected and not CORS-open, so live fetching happens server-side: you copy the config and run the export live on the backing Apify actor.

The backing actor runs on Apify, which gives new accounts free platform credits to start, so you can test before committing spend. The actor itself bills pay-as-you-go on a pay-per-event basis — for example per car listing extracted — rather than a flat subscription, and you control spend with maxListingsPerPlatform. Always check the current pricing on the actor's Apify Store page before a large run.

Set the make field to a brand (for example Toyota, Mercedes-Benz, Nissan or Lexus — among the most listed brands in Dubai) and model to a specific model (for example Land Cruiser or Patrol). Filtering by model requires a make to be set; model alone is ignored. Leave both empty to scan the entire market across the selected platforms. The filters narrow the export so you only pay for and download the segment you care about.

Each record can include vehicle details (make, model, year, trim, bodyType, mileageKm, fuelType, transmission, engineSize, color), pricing and location (price, currency AED, city, country), seller information (sellerType, dealerName, isGccSpec, inspected) and listing metadata (listingUrl, title, images, listingDate, scrapedAt). Not every field is present on every row — values are populated when the source listing exposes them and are otherwise null. The preview on this page shows the full shape so you can map fields before you run.

Yes. The backing actor has a change-detection mode: when you run the same query on a schedule against a named dataset (set the same datasetName each run), it compares the new run with the previous one and flags listings whose price changed, plus new and removed listings and cross-platform relistings. Detected changes are billed per change in addition to the per-listing charge. This builder produces the base query you would schedule; you enable change detection and set the dataset name on the actor itself.

Scraping publicly visible listing data is generally lower-risk than accessing private or login-gated content, but you remain responsible for compliance. Review each platform's terms of service, avoid republishing copyrighted images or full descriptions, respect rate limits, and use the data for analysis rather than wholesale copying. For commercial use, confirm your specific use case with counsel.

Any official data feeds the marketplaces may offer tend to be commercial, enterprise-oriented products rather than self-serve. This tool is a self-serve, pay-as-you-go alternative for developers and analysts who want a specific make/model slice or a quick market snapshot without an enterprise contract — and it normalizes multiple platforms into one schema in a single run.