A cleaned database of the hammer prices of 750,000+ heavy equipment and truck lots auctioned between 2024 and 2026 in North America, Europe, Australia and the Middle East. One record per lot, with normalised make and model, year, hours or kilometres, sale date, country and original currency. For appraisers, dealers, lenders, insurers and fleets.
Quick answer: A cleaned database of the hammer prices of 750,000+ heavy equipment and truck lots auctioned between 2024 and 2026, with normalised make and model, year, hours or kilometres, sale date, country and original currency, filterable by category, make, model and date. Sample of 100 rows in CSV and JSON.
Asking prices are inflated and dealer prices are not published. The hammer price is what someone actually paid.
| Block | Fields | What it holds |
|---|---|---|
| Price | price · currency · lot_qty · price_per_unit | Hammer price in the auction currency (USD, CAD, EUR, AUD, GBP…) and unit price for multi-unit lots |
| Machine | make · model · model_key · model_family · year | Normalised make and model (M2 106 = M2106) and family to group comparables (D6T, D6N → d6) |
| Usage and condition | usage · unused · inoperable · spec_main | Hours or kilometres at sale, unused, inoperable and main size or capacity |
| Classification | industry · category · asset_type | Construction › Excavators › Crawler excavator |
| Sale | sold_at · country · bid_count | Date and time, auction country and number of bids |
| Traceability | make_source · model_source · year_source · _data_version | Whether the value came from the listing or was inferred from the title, and monthly database version |
Cleaned before it is served. One record per lot, no duplicates; only lots with a usable make and model; loose parts, attachments and non-machine lots excluded. When make, model or year are inferred from the title, the *_source fields say so: flagged, never hidden.
Queries in seconds. No waiting for a scrape: the database is rebuilt monthly and every run filters by category, make, model, sale date, year of manufacture and country.
Six real use cases: who uses them, what you do and which fields you need.
model_family, year, usage, price, sold_atcategory, make, year, price, sold_atmodel, year, usage, price, countrymodel_family, year, usage, price, bid_countyear, usage, price, categorysold_at, category, make, country, priceA single 600-row query, in five seconds and for under 2 dollars.
| Model (family) | Sales | Years | 25th percentile | 75th percentile | Maximum |
|---|---|---|---|---|---|
| Komatsu PC360 | 26 | 2015–2024 | 25,875 $ | 62,250 $ | 170,000 $ |
| Caterpillar 336 | 21 | 2019–2024 | 99,000 $ | 228,750 $ | 278,000 $ |
| Caterpillar 308E | 21 | 2015–2019 | 31,000 $ | 44,500 $ | 52,000 $ |
| Caterpillar 3055E | 18 | 2015–2021 | 25,250 $ | 34,250 $ | 52,000 $ |
| Komatsu PC210 | 16 | 2015–2024 | 36,500 $ | 84,000 $ | 167,500 $ |
| Komatsu PC490 | 16 | 2016–2021 | 34,250 $ | 61,500 $ | 76,000 $ |
| Caterpillar 336FL | 15 | 2015–2018 | 50,000 $ | 76,000 $ | 125,000 $ |
| Caterpillar 3035E | 12 | 2015–2021 | 16,000 $ | 26,750 $ | 29,000 $ |
The 600 most recent sales of Caterpillar and Komatsu excavators built since 2015 (unused excluded), sold June to October 2026; single-unit lots sold in US dollars only. The middle half of sales falls between the 25th and 75th percentiles.
The spread within one model is wide because year, hours and condition weigh heavily: that is why you work with comparables rather than one price. Sales arrive in their original currency (372 in US dollars, 103 in Canadian dollars and the rest in euros, pounds and Australian dollars), so you can apply your own exchange rate.
100 of the query's 600 sales in the public sample, which downloads without signing up.
| sold_at | make | model | year | usage | price | currency | country | bid_count |
|---|---|---|---|---|---|---|---|---|
| 2026-10-08 | Caterpillar | 302CR | 2022 | 902.0 h | 18500 | USD | US | 9 |
| 2026-10-08 | Caterpillar | 303 CR | 2024 | 1398.0 h | 21250 | USD | US | 59 |
| 2026-10-08 | Caterpillar | 320 | 2019 | 3994.0 h | 70000 | USD | US | 26 |
| 2026-10-08 | Caterpillar | 330-07 | 2024 | 1834.0 h | 266000 | CAD | CA | 81 |
| 2026-10-08 | Caterpillar | 306CR | 2021 | 1562.0 h | 35000 | USD | US | 20 |
| 2026-10-08 | Caterpillar | 325 | 2021 | 9377.0 h | 75000 | USD | US | 1 |
| 2026-10-08 | Komatsu | PC360LC 11 | 2016 | 8719.0 h | 25500 | USD | US | 29 |
| 2026-10-08 | Caterpillar | M318 | 2020 | 3048.0 h | 139000 | USD | US | 171 |
Real rows from the "Caterpillar and Komatsu excavators since 2015, sold since January 2025" task.
Paste the input into the actor's JSON tab and press Start. Pick at least one category, industry or make.
| Task | Input (JSON) | What it is for |
|---|---|---|
| Cat and Komatsu excavators | {"category": ["Excavators"], "make": ["Caterpillar", "Komatsu"], "soldFrom": "2025-01", "yearMin": 2015, "excludeUnused": true, "maxItems": 20} | Saved task, as a 20-row test run. |
| One specific model | {"category": ["Dozers"], "make": ["Caterpillar"], "model": "D6", "soldFrom": "2025-01"} | Comparables for an appraisal. |
| Truck tractors | {"category": ["Truck Tractors"], "model": "Cascadia 125", "yearMin": 2019} | Residual value of a truck fleet. |
| European auctions only | {"industry": ["Construction"], "country": ["NL", "GB", "IT", "FR", "ES"], "soldFrom": "2026-01"} | Prices in euros and pounds. |
| All excavators in one file | {"category": ["Excavators"], "outputMode": "file", "fileFormat": "parquet"} | Bulk export, 60 % cheaper per row. |
| Used forklifts | {"industry": ["Forklifts"], "excludeUnused": true, "soldFrom": "2025-06"} | Material-handling market. |
In row mode you get up to 200,000 records, most recent first; in file mode, everything matching the filter in one Parquet or CSV.
One row per sold lot.
| Field | Description |
|---|---|
sold_at · sold_year | Date and time of the sale |
make · model · model_key · model_family | Make, model, normalised model and family |
year · usage | Year of manufacture and hours or kilometres |
price · currency · lot_qty · price_per_unit | Hammer price, currency, units in the lot and unit price |
industry · category · asset_type · spec_main | Industry, category, type and size or capacity |
country · bid_count · buying_format | Auction country, number of bids and sale format |
unused · inoperable | Unused / inoperable |
make_source · model_source · year_source | original or inferred from the title |
asset_description | Lot title |
_data_version | Monthly database version |
You only pay for the data you get.
| Event | Price |
|---|---|
| Actor start | $0.005 |
| Database query (once per run with data) | $0.03 |
| Dataset row | $0.0025 |
| Exported row (file mode) | $0.001 |
Examples: 1,000 sales of one model, about $2.54; every excavator (57,000+) in one Parquet, about $57.80.
From public results of completed heavy equipment and truck auctions, on-site and online. No login-protected data is used. The source is stated on the actor's Apify listing.
The database is rebuilt monthly; _data_version shows the version. Auctions from the last few weeks enter the next update.
No. Every sale keeps the auction's original currency, so you can apply your own exchange rate and date.
To keep queries fast and focused. For the whole database there is file mode, which exports everything to one Parquet or CSV.
That is its main use. For an individual appraisal, combine sold prices with the machine's condition, hours and inspection.
An asking price is what the seller wants; a hammer price is what the buyer paid. To compare both, this site has the used-machinery marketplaces of Europe and China.
Tell us which categories, makes or models you want to value and we will send an extract in the schema you would receive.