Data Storage (DTST) Operating Expenses (2010 - 2026)
Data Storage's Operating Expenses came in at $1.45 million for Q2 2026, up 33.2% from $1.09 million a year earlier but down 1.5% from the prior quarter.
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Analysis
Data Storage (DTST) Operating Expenses (2010 - 2026) Analysis & Trends
Over the trailing twelve months to Jun 30, 2026, Data Storage reported Operating Expenses of $10.55 million, up 170.2% year-over-year; for FY2025, it came in at $4.19 million, up 9.1% from FY2024.
- Operating Expenses carries a five-year compound annual growth rate of 1.5% (FY2020 to FY2025).
- Going back by year, Operating Expenses was $3.84 million in FY2024 (-60.6%), $9.74 million in FY2023 (-0.9%), $9.84 million in FY2022 (+36.9%) and $7.18 million in FY2021 (+84.4%).
- The five-year range for quarterly Operating Expenses is $856,915 (Q1 2025) to $6.68 million (Q3 2025).
- Year-over-year, Operating Expenses increased in two of the last seven quarters, with an average decline of 21.6%.
- The fastest year-over-year change in Operating Expenses over five years came in Q4 2021 (growth of 159.8%), and the weakest in Q1 2025 (a decline of 68.9%).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Apple | 4,865.08 Bn | 4,612.57 Bn | 54.77 Bn | 19.08 Bn |
| 2 | Cisco Systems | 424.71 Bn | 360.64 Bn | 11.06 Bn | 6.80 Bn |
| 3 | Dell Technologies | 344.52 Bn | 300.28 Bn | 9.83 Bn | 4.45 Bn |
| 4 | Arista Networks | 256.79 Bn | 210.25 Bn | 1.91 Bn | 532.30 Mn |
| 5 | Sandisk | 254.02 Bn | 242.55 Bn | 7.58 Bn | 545.00 Mn |
| 6 | Seagate Technology Holdings | 209.18 Bn | 204.17 Bn | 1.90 Bn | 2.07 Bn |
| 7 | Western Digital | 164.06 Bn | 152.19 Bn | 2.03 Bn | 465.00 Mn |
| 8 | Sony | 144.83 Bn | 95.22 Bn | 6.53 Bn | 14.83 Bn |
| 9 | Lumentum Holdings | 86.05 Bn | 77.87 Bn | 477.30 Mn | 198.00 Mn |
| 10 | Data Storage | 7.72 Mn | 7.50 Mn | 168,481.00 | 1.45 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 1.45 Mn |
| Mar 31, 2026 | 1.47 Mn |
| Dec 31, 2025 | 945,193.00 |
| Sep 30, 2025 | 1.30 Mn |
| Jun 30, 2025 | 1.09 Mn |
| Mar 31, 2025 | 856,915.00 |
| Dec 31, 2024 | 973,228.00 |
| Sep 30, 2024 | 984,099.00 |
| Jun 30, 2024 | 2.80 Mn |
| Mar 31, 2024 | 2.75 Mn |
| Dec 31, 2023 | 2.83 Mn |
| Sep 30, 2023 | 2.32 Mn |
| Jun 30, 2023 | 2.47 Mn |
| Mar 31, 2023 | 2.13 Mn |
| Dec 31, 2022 | 2.71 Mn |
| Sep 30, 2022 | 2.08 Mn |
| Jun 30, 2022 | 2.59 Mn |
| Mar 31, 2022 | 2.46 Mn |
| Dec 31, 2021 | 2.63 Mn |
| Sep 30, 2021 | 1.87 Mn |
API Access
Data Storage 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=DTST&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "DTST", "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=DTST&period=max&api_key=YOUR_API_KEY");
const data = await res.json();