Docebo (DCBO) EBITDA (2019 - 2026)
Docebo (DCBO) posted EBITDA of $4.78 million for the quarter ended Jun 30, 2026, down 4.1% from $4.99 million a year earlier.
Docebo (DCBO) EBITDA (2019 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, EBITDA at Docebo was $24.48 million, up 12.4% year-over-year; for the year ended Dec 31, 2025, it came in at $26.42 million, up 7.1% from the prior year.
- In prior years, Docebo's EBITDA was $24.68 million in the year ended Dec 31, 2024, -$569,000 in the year ended Dec 31, 2023, $6.52 million in the year ended Dec 31, 2022 and -$11.43 million in the year ended Dec 31, 2021.
- Quarterly EBITDA has run from a low of -$12.89 million in the quarter ended Dec 31, 2021 to a high of $10.3 million in the quarter ended Dec 31, 2025 over five years.
- On a year-over-year basis, EBITDA increased in three of the last seven quarters, with an average decline of 4.4%.
- The strongest year-over-year quarter for EBITDA in the past five years was the quarter ended Sep 30, 2022, with growth of 387.9%; the weakest was the quarter ended Mar 31, 2026, with a decline of 82.9%.
- According to Business Quant data, EBITDA for the three prior quarters was $429,000 (quarter ended Mar 31, 2026), $10.3 million (quarter ended Dec 31, 2025) and $8.97 million (quarter ended Sep 30, 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Bryn | 945.00 Bn | 945.00 Bn | - | - |
| 2 | Veeva Systems | 51.94 Bn | 24.18 Bn | 695.95 Mn | 290.79 Mn |
| 3 | Samsara | 25.33 Bn | 22.10 Bn | 392.58 Mn | 13.29 Mn |
| 4 | Ptc | 22.23 Bn | 21.05 Bn | 490.47 Mn | 190.70 Mn |
| 5 | Toast | 19.17 Bn | 11.84 Bn | 516.00 Mn | 188.00 Mn |
| 6 | Trimble | 14.59 Bn | 13.66 Bn | 674.90 Mn | 183.10 Mn |
| 7 | Manhattan Associates | 13.85 Bn | 12.85 Bn | 168.33 Mn | 67.86 Mn |
| 8 | Costar | 13.39 Bn | 7.34 Bn | 728.00 Mn | 191.00 Mn |
| 9 | Bentley Systems | 12.01 Bn | 11.47 Bn | 336.74 Mn | 105.71 Mn |
| 10 | Docebo | 880.21 Mn | 631.14 Mn | 54.53 Mn | 4.78 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 4.78 Mn |
| Mar 31, 2026 | 429,000.00 |
| Dec 31, 2025 | 10.30 Mn |
| Sep 30, 2025 | 8.97 Mn |
| Jun 30, 2025 | 4.99 Mn |
| Mar 31, 2025 | 2.51 Mn |
| Dec 31, 2024 | 8.69 Mn |
| Sep 30, 2024 | 5.59 Mn |
| Jun 30, 2024 | 5.35 Mn |
| Mar 31, 2024 | 5.05 Mn |
| Dec 31, 2023 | 1.63 Mn |
| Sep 30, 2023 | 4.17 Mn |
| Jun 30, 2023 | -6.70 Mn |
| Mar 31, 2023 | 331,000.00 |
| Dec 31, 2022 | 527,000.00 |
| Sep 30, 2022 | 9.59 Mn |
| Jun 30, 2022 | 2.69 Mn |
| Mar 31, 2022 | -6.29 Mn |
| Dec 31, 2021 | -2.39 Mn |
| Sep 30, 2021 | 1.97 Mn |
Docebo 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=DCBO&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "DCBO", "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=DCBO&period=max&api_key=YOUR_API_KEY");
const data = await res.json();