Table Trac (TBTC) Operating Expenses (2010 - 2026)
Table Trac (TBTC) posted Operating Expenses of $1.77 million for Q2 2026, up 3.8% from $1.7 million a year earlier and up 17.8% from the prior quarter.
Table Trac (TBTC) Operating Expenses (2010 - 2026) Analysis & Trends
For the trailing twelve months through Jun 30, 2026, Operating Expenses at Table Trac was $6.46 million, down 1.6% year-over-year; for FY2025, it came in at $6.55 million, up 6.1% from FY2024.
- Annual Operating Expenses has increased for four consecutive years, with a five-year compound annual growth rate of 12.3% (FY2020 to FY2025).
- In prior years, Table Trac's Operating Expenses was $6.18 million in FY2024 (+14.9%), $5.37 million in FY2023 (+9.0%), $4.93 million in FY2022 (+38.4%) and $3.56 million in FY2021 (-3.0%).
- The Q2 2026 figure stands as the highest quarterly Operating Expenses in data going back to Q2 2010.
- On a year-over-year basis, Operating Expenses increased in six of the last eight quarters, with growth averaging 7.9%.
- The strongest year-over-year quarter for Operating Expenses in the past five years was Q4 2022, with growth of 75.1%; the weakest was Q4 2023, with a decline of 17.3%.
- According to Business Quant data, Operating Expenses for the three prior quarters was $1.5 million (Q1 2026), $1.57 million (Q4 2025) and $1.62 million (Q3 2025).
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Bryn | 945.00 Bn | 945.00 Bn | - | 178,646.00 |
| 2 | Veeva Systems | 51.55 Bn | 23.79 Bn | 695.95 Mn | 420.93 Mn |
| 3 | Samsara | 24.79 Bn | 21.56 Bn | 392.58 Mn | 387.71 Mn |
| 4 | Ptc | 22.17 Bn | 20.99 Bn | 490.47 Mn | 323.96 Mn |
| 5 | Toast | 18.88 Bn | 11.55 Bn | 516.00 Mn | 364.00 Mn |
| 6 | Trimble | 14.47 Bn | 13.54 Bn | 674.90 Mn | 542.90 Mn |
| 7 | Manhattan Associates | 13.68 Bn | 12.67 Bn | 168.33 Mn | 231.56 Mn |
| 8 | Costar | 13.35 Bn | 7.30 Bn | 728.00 Mn | 652.00 Mn |
| 9 | Bentley Systems | 11.88 Bn | 11.34 Bn | 336.74 Mn | 248.13 Mn |
| 10 | Table Trac | 25.21 Mn | -7.56 Mn | 2.96 Mn | 1.77 Mn |
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.77 Mn |
| Mar 31, 2026 | 1.50 Mn |
| Dec 31, 2025 | 1.57 Mn |
| Sep 30, 2025 | 1.62 Mn |
| Jun 30, 2025 | 1.70 Mn |
| Mar 31, 2025 | 1.66 Mn |
| Dec 31, 2024 | 1.67 Mn |
| Sep 30, 2024 | 1.53 Mn |
| Jun 30, 2024 | 1.49 Mn |
| Mar 31, 2024 | 1.49 Mn |
| Dec 31, 2023 | 1.34 Mn |
| Sep 30, 2023 | 1.29 Mn |
| Jun 30, 2023 | 1.20 Mn |
| Mar 31, 2023 | 1.54 Mn |
| Dec 31, 2022 | 1.62 Mn |
| Sep 30, 2022 | 1.09 Mn |
| Jun 30, 2022 | 1.13 Mn |
| Mar 31, 2022 | 1.09 Mn |
| Dec 31, 2021 | 923,456.00 |
| Sep 30, 2021 | 753,980.00 |
Table Trac Operating Expenses 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=operating-expenses&ticker=TBTC&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "TBTC", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()
const res = await fetch("https://data.businessquant.com/historic?slug=operating-expenses&ticker=TBTC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();