Sps Commerce (SPSC) Total Liabilities (2010 - 2026)
Sps Commerce (SPSC) posted Total Liabilities of $186.95 million for Q2 2026, up 9.1% from $171.32 million a year earlier but down 6.1% from the prior quarter.
Sps Commerce (SPSC) Total Liabilities (2010 - 2026) Analysis & Trends
At the end of FY2025, Sps Commerce's Total Liabilities came in at $195.97 million, up 11.0% from FY2024.
- Annual Total Liabilities has increased for ten consecutive years, with a five-year compound annual growth rate of 13.1% (FY2020 to FY2025).
- In prior years, Sps Commerce's Total Liabilities was $176.54 million in FY2024 (+12.9%), $156.37 million in FY2023 (+15.1%), $135.84 million in FY2022 (+3.2%) and $131.59 million in FY2021 (+24.4%).
- Quarterly Total Liabilities has run from a low of $120.76 million in Q3 2021 to a high of $199.74 million in Q3 2025 over five years.
- On a year-over-year basis, Total Liabilities has increased in each of the last 20 quarters, with growth averaging 11.9% over the last eight quarters.
- The year-over-year growth in Total Liabilities has ranged between 3.2% (Q4 2022) and 30.2% (Q3 2021) over the last five years.
- According to Business Quant data, Total Liabilities for the three prior quarters was $199.05 million (Q1 2026), $195.97 million (Q4 2025) and $199.74 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Total Liabilities (Qtr) |
|---|---|---|---|---|---|
| 1 | Bryn | 945.00 Bn | 945.00 Bn | - | 206,169.00 |
| 2 | Veeva Systems | 45.35 Bn | 17.59 Bn | 695.95 Mn | 1.63 Bn |
| 3 | Samsara | 22.20 Bn | 18.97 Bn | 392.58 Mn | 1.17 Bn |
| 4 | Toast | 17.53 Bn | 10.20 Bn | 516.00 Mn | 1.14 Bn |
| 5 | Ptc | 15.47 Bn | 14.28 Bn | 490.47 Mn | 3.04 Bn |
| 6 | Trimble | 13.41 Bn | 12.48 Bn | 674.90 Mn | 3.43 Bn |
| 7 | Duolingo | 12.56 Bn | 7.73 Bn | 216.74 Mn | 664.21 Mn |
| 8 | Manhattan Associates | 11.77 Bn | 10.77 Bn | 168.33 Mn | 541.14 Mn |
| 9 | Costar | 10.95 Bn | 4.91 Bn | 728.00 Mn | 2.19 Bn |
| 10 | Sps Commerce | 2.93 Bn | 2.32 Bn | 138.79 Mn | 186.95 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 186.95 Mn |
| Mar 31, 2026 | 199.05 Mn |
| Dec 31, 2025 | 195.97 Mn |
| Sep 30, 2025 | 199.74 Mn |
| Jun 30, 2025 | 171.32 Mn |
| Mar 31, 2025 | 188.13 Mn |
| Dec 31, 2024 | 176.54 Mn |
| Sep 30, 2024 | 173.94 Mn |
| Jun 30, 2024 | 151.10 Mn |
| Mar 31, 2024 | 156.88 Mn |
| Dec 31, 2023 | 156.37 Mn |
| Sep 30, 2023 | 160.56 Mn |
| Jun 30, 2023 | 134.56 Mn |
| Mar 31, 2023 | 131.04 Mn |
| Dec 31, 2022 | 135.84 Mn |
| Sep 30, 2022 | 129.43 Mn |
| Jun 30, 2022 | 125.76 Mn |
| Mar 31, 2022 | 121.79 Mn |
| Dec 31, 2021 | 131.59 Mn |
| Sep 30, 2021 | 120.76 Mn |
Sps Commerce Total Liabilities 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=total-liabilities&ticker=SPSC&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "total-liabilities", "ticker": "SPSC", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=total-liabilities&ticker=SPSC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();