Dollar Tree (DLTR) EBITDA (2009 - 2026)
Dollar Tree's EBITDA came in at $869.9 million for fiscal Q2 2027 (quarter ended Aug 1, 2026), up 121.3% from $393 million a year earlier and up 33.8% from the prior quarter.
Dollar Tree (DLTR) EBITDA (2009 - 2026) Analysis & Trends
Over the trailing twelve months to Aug 1, 2026, Dollar Tree reported EBITDA of $2.89 billion, up 39.2% year-over-year; for FY2026 (ended Jan 31, 2026), it came in at $2.3 billion, up 15.7% from FY2025.
- EBITDA carries a five-year compound annual growth rate of -2.2% (FY2021 to FY2026).
- Going back by fiscal year, EBITDA was $1.99 billion in FY2025 (-8.6%), $2.18 billion in FY2024 (-11.8%), $2.46 billion in FY2023 (-2.5%) and $2.53 billion in FY2022 (-1.8%).
- The fiscal Q2 2027 figure represents the highest quarterly EBITDA since fiscal Q1 2023.
- Year-over-year, EBITDA has increased for seven consecutive quarters, with growth averaging 26.9% over the last eight quarters.
- The fastest year-over-year change in EBITDA over five years came in fiscal Q2 2027 (growth of 121.3%), and the weakest in fiscal Q4 2023 (a decline of 64.2%).
- Business Quant data shows DLTR's EBITDA at $650.3 million (Q1 2027), $865.2 million (Q4 2026) and $507.8 million (Q3 2026) in the three fiscal quarters before Q2 2027.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Walmart | 862.64 Bn | 825.34 Bn | 49.13 Bn | 13.31 Bn |
| 2 | Costco Wholesale | 409.33 Bn | 338.62 Bn | 9.01 Bn | 3.41 Bn |
| 3 | Sysco | 37.65 Bn | 31.90 Bn | 4.13 Bn | 1.24 Bn |
| 4 | Kroger | 35.26 Bn | 21.42 Bn | 7.86 Bn | 1.71 Bn |
| 5 | Dollar General | 27.43 Bn | 22.11 Bn | 3.68 Bn | 1.05 Bn |
| 6 | Caseys General Stores | 22.41 Bn | 20.40 Bn | 1.24 Bn | 601.08 Mn |
| 7 | Dollar Tree | 21.77 Bn | 18.40 Bn | 2.10 Bn | 869.90 Mn |
| 8 | US Foods Holding | 20.27 Bn | 20.06 Bn | 1.92 Bn | 561.00 Mn |
| 9 | Tractor Supply | 16.74 Bn | 15.90 Bn | 1.68 Bn | 597.96 Mn |
| 10 | Performance Food | 14.36 Bn | 14.14 Bn | 2.17 Bn | 537.40 Mn |
Historic Data
| Date | Value |
|---|---|
| Aug 1, 2026 | 869.90 Mn |
| May 2, 2026 | 650.30 Mn |
| Jan 31, 2026 | 865.20 Mn |
| Nov 1, 2025 | 507.80 Mn |
| Aug 2, 2025 | 393.00 Mn |
| May 3, 2025 | 535.20 Mn |
| Feb 1, 2025 | 683.40 Mn |
| Nov 2, 2024 | 466.20 Mn |
| Aug 3, 2024 | 338.40 Mn |
| May 4, 2024 | 500.90 Mn |
| Feb 3, 2024 | 551.00 Mn |
| Oct 28, 2023 | 517.50 Mn |
| Jul 29, 2023 | 490.40 Mn |
| Apr 29, 2023 | 616.10 Mn |
| Jan 28, 2023 | 275.00 Mn |
| Oct 29, 2022 | 570.30 Mn |
| Jul 30, 2022 | 698.90 Mn |
| Apr 30, 2022 | 920.40 Mn |
| Jan 29, 2022 | 767.50 Mn |
| Oct 30, 2021 | 489.00 Mn |
Dollar Tree EBITDA 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=ebitda&ticker=DLTR&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "DLTR", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=ebitda&ticker=DLTR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();