Dingdong (Cayman) (DDL) Receivables (2020 - 2026)
Dingdong (Cayman) (DDL) posted Receivables of $3.56 million for the quarter ended Jun 30, 2026, down 81.4% from $19.11 million a year earlier and down 40.8% from the prior quarter.
Dingdong (Cayman) (DDL) Receivables (2020 - 2026) Analysis & Trends
As of Dec 31, 2025, Dingdong (Cayman)'s Receivables came in at $6.87 million, down 60.2% from the prior year.
- Annual Receivables shows a five-year compound annual growth rate of -0.6% (years ended Dec 2020 to Dec 2025).
- In prior years, Dingdong (Cayman)'s Receivables was $17.25 million in the year ended Dec 31, 2024 (+13.5%), $15.19 million in the year ended Dec 31, 2023 (-25.9%), $20.51 million in the year ended Dec 31, 2022 (-99.9%) and $30.05 billion in the year ended Dec 31, 2021.
- The figure for the quarter ended Jun 30, 2026 stands as the lowest quarterly Receivables in data going back to the quarter ended Dec 31, 2020.
- On a year-over-year basis, Receivables has declined in each of the last three quarters, with an average decline of 13.0% over the last eight quarters.
- The strongest year-over-year quarter for Receivables in the past five years was the quarter ended Dec 31, 2021, with growth of 305.9%; the weakest was the quarter ended Jun 30, 2026, with a decline of 81.4%.
- According to Business Quant data, Receivables for the three prior quarters was $6.01 million (quarter ended Mar 31, 2026), $6.87 million (quarter ended Dec 31, 2025) and $24.87 million (quarter ended Sep 30, 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Receivables (Qtr) |
|---|---|---|---|---|---|
| 1 | Walmart | 824.47 Bn | 787.18 Bn | 49.13 Bn | 11.08 Bn |
| 2 | Costco Wholesale | 403.75 Bn | 333.05 Bn | 9.01 Bn | 3.75 Bn |
| 3 | Sysco | 37.36 Bn | 31.61 Bn | 4.13 Bn | 11.37 Bn |
| 4 | Kroger | 34.63 Bn | 20.79 Bn | 7.86 Bn | 2.19 Bn |
| 5 | Dollar General | 26.38 Bn | 21.06 Bn | 3.68 Bn | - |
| 6 | Caseys General Stores | 22.49 Bn | 20.48 Bn | 1.24 Bn | 245.84 Mn |
| 7 | Dollar Tree | 21.40 Bn | 18.02 Bn | 2.10 Bn | - |
| 8 | US Foods Holding | 19.94 Bn | 19.74 Bn | 1.92 Bn | 2.48 Bn |
| 9 | Tractor Supply | 16.33 Bn | 15.49 Bn | 1.68 Bn | - |
| 10 | Dingdong (Cayman) | 1.39 Bn | 114.26 Mn | 1.64 Mn | 3.56 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 3.56 Mn |
| Mar 31, 2026 | 6.01 Mn |
| Dec 31, 2025 | 6.87 Mn |
| Sep 30, 2025 | 24.87 Mn |
| Jun 30, 2025 | 19.11 Mn |
| Mar 31, 2025 | 18.58 Mn |
| Dec 31, 2024 | 17.53 Mn |
| Sep 30, 2024 | 18.99 Mn |
| Jun 30, 2024 | 15.48 Mn |
| Mar 31, 2024 | 14.53 Mn |
| Dec 31, 2023 | 14.98 Mn |
| Sep 30, 2023 | 17.84 Mn |
| Jun 30, 2023 | 14.77 Mn |
| Mar 31, 2023 | 15.19 Mn |
| Dec 31, 2022 | 19.89 Mn |
| Sep 30, 2022 | 22.67 Mn |
| Jun 30, 2022 | 23.62 Mn |
| Mar 31, 2022 | 40.58 Mn |
| Dec 31, 2021 | 29.96 Mn |
| Sep 30, 2021 | 23.83 Mn |
Dingdong (Cayman) Receivables API
Pull this series into your own models, spreadsheets and apps with the Business Quant
Historical Metrics API. The request below matches the chart above — change the
frequency, period or values and it follows. Swap YOUR_API_KEY for your own key.
https://data.businessquant.com/historic?slug=receivables&ticker=DDL&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "receivables", "ticker": "DDL", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=receivables&ticker=DDL&period=max&api_key=YOUR_API_KEY");
const data = await res.json();