Manhattan Associates (MANH) EBITDA (2010 - 2026)
Manhattan Associates' (MANH) quarterly EBITDA came in at $66.2 million in Q2 2026, down 10.24% year-over-year from $73.8 million in Q2 2025, and up 1.99% quarter-over-quarter from $64.9 million in Q1 2026.
Manhattan Associates (MANH) EBITDA (2010 - 2026) Analysis & Trends
Manhattan Associates has disclosed EBITDA across 17 years of filings, most recently posting $66.2 million for Q2 2026.
- In Q2 2026, EBITDA fell 10.24% year-over-year to $66.2 million; the TTM figure through Jun 2026 stood at $274.0 million (changed 0.47% YoY), while the FY2025 annual figure was $279.8 million, up 6.96% from the prior year.
- EBITDA came in at $66.2 million for Q2 2026 at Manhattan Associates, up from $64.9 million in the prior quarter.
- In the past five years, EBITDA ranged from a high of $75.8 million in Q3 2025 to a low of $34.0 million in Q1 2022.
- Average EBITDA over 5 years is $57.5 million, with a median of $59.8 million recorded in 2023.
- The largest YoY upside for EBITDA was 64.7% in 2022 against a maximum downside of 13.29% in 2022.
- Over 5 years, EBITDA stood at $44.7 million in 2022, then surged by 31.67% to $58.9 million in 2023, then gained by 3.1% to $60.7 million in 2024, then climbed by 10.42% to $67.0 million in 2025, then retreated by 1.17% to $66.2 million in 2026.
- Per Business Quant data, the three most recent EBITDA figures were $66.2 million in Q2 2026, $64.9 million in Q1 2026, and $67.0 million in Q4 2025.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | EBITDA (Qtr) |
|---|---|---|---|---|---|
| 1 | Veeva Systems | 43.86 Bn | 36.61 Bn | 695.95 Mn | 275.02 Mn |
| 2 | Samsara | 22.87 Bn | 22.04 Bn | 392.58 Mn | 4.88 Mn |
| 3 | Toast | 17.21 Bn | 15.49 Bn | 516.00 Mn | 152.00 Mn |
| 4 | Ptc | 15.54 Bn | 15.19 Bn | 490.47 Mn | 166.51 Mn |
| 5 | Trimble | 13.83 Bn | 13.62 Bn | 674.90 Mn | 132.00 Mn |
| 6 | Duolingo | 13.65 Bn | 12.34 Bn | 216.74 Mn | 33.95 Mn |
| 7 | Manhattan Associates | 12.26 Bn | 12.08 Bn | 168.33 Mn | 66.23 Mn |
| 8 | Costar | 11.45 Bn | 10.20 Bn | 728.00 Mn | 76.00 Mn |
| 9 | Bentley Systems | 9.87 Bn | 9.73 Bn | 336.74 Mn | 88.61 Mn |
| 10 | Procore Technologies | 7.76 Bn | 7.10 Bn | 299.80 Mn | 4.33 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 67.86 Mn |
| Mar 31, 2026 | 66.77 Mn |
| Dec 31, 2025 | 68.54 Mn |
| Sep 30, 2025 | 77.49 Mn |
| Jun 30, 2025 | 75.37 Mn |
| Mar 31, 2025 | 64.71 Mn |
| Dec 31, 2024 | 62.32 Mn |
| Sep 30, 2024 | 76.78 Mn |
| Jun 30, 2024 | 69.68 Mn |
| Mar 31, 2024 | 59.12 Mn |
| Dec 31, 2023 | 60.42 Mn |
| Sep 30, 2023 | 54.89 Mn |
| Jun 30, 2023 | 51.80 Mn |
| Mar 31, 2023 | 48.57 Mn |
| Dec 31, 2022 | 46.25 Mn |
| Sep 30, 2022 | 38.43 Mn |
| Jun 30, 2022 | 39.00 Mn |
| Mar 31, 2022 | 35.72 Mn |
| Dec 31, 2021 | 28.92 Mn |
| Sep 30, 2021 | 44.33 Mn |
Manhattan Associates 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=MANH&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "ebitda", "ticker": "MANH", "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=MANH&period=max&api_key=YOUR_API_KEY");
const data = await res.json();