Elastic (ESTC) Accumulated Expenses (2018 - 2026)
Elastic (ESTC) posted Accumulated Expenses of $77.92 million for fiscal Q1 2027 (quarter ended Jul 31, 2026), up 6.3% from $73.3 million a year earlier but down 19.4% from the prior quarter.
Powered by 
Analysis
Elastic (ESTC) Accumulated Expenses (2018 - 2026) Analysis & Trends
At the end of FY2026 (ended Apr 30, 2026), Elastic's Accumulated Expenses came in at $96.71 million, up 12.0% from FY2025.
- Annual Accumulated Expenses has increased for eight consecutive fiscal years, with a five-year compound annual growth rate of 27.3% (FY2021 to FY2026).
- In prior fiscal years, Elastic's Accumulated Expenses was $86.35 million in FY2025 (+14.7%), $75.29 million in FY2024 (+18.5%), $63.53 million in FY2023 (+17.8%) and $53.93 million in FY2022 (+86.6%).
- Quarterly Accumulated Expenses has run from a low of $42.11 million in fiscal Q3 2022 to a high of $100.93 million in fiscal Q2 2026 over five years.
- On a year-over-year basis, Accumulated Expenses has increased in each of the last 20 quarters, with growth averaging 14.6% over the last eight quarters.
- Across the past five years, year-over-year growth in Accumulated Expenses ran from 1.2% in fiscal Q1 2026 to 86.6% in fiscal Q4 2022.
- According to Business Quant data, Accumulated Expenses for the three prior fiscal quarters was $96.71 million (Q4 2026), $86.12 million (Q3 2026) and $100.93 million (Q2 2026).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) |
|---|---|---|---|---|
| 1 | Palo Alto Networks | 323.81 Bn | 308.88 Bn | 2.30 Bn |
| 2 | CrowdStrike Holdings | 271.09 Bn | 251.53 Bn | 1.10 Bn |
| 3 | Fortinet | 131.14 Bn | 117.07 Bn | 1.64 Bn |
| 4 | Snowflake | 119.71 Bn | 107.03 Bn | 1.04 Bn |
| 5 | Datadog | 98.30 Bn | 79.94 Bn | 881.34 Mn |
| 6 | Okta | 34.95 Bn | 25.05 Bn | 641.00 Mn |
| 7 | Axon Enterprise | 34.32 Bn | 28.85 Bn | 546.45 Mn |
| 8 | Zscaler | 32.52 Bn | 18.64 Bn | - |
| 9 | Baidu | 29.56 Bn | -44.07 Bn | 1.47 Mn |
| 10 | Elastic | 9.64 Bn | 4.16 Bn | 356.19 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | 77.92 Mn |
| Apr 30, 2026 | 96.71 Mn |
| Jan 31, 2026 | 86.12 Mn |
| Oct 31, 2025 | 100.93 Mn |
| Jul 31, 2025 | 73.30 Mn |
| Apr 30, 2025 | 86.35 Mn |
| Jan 31, 2025 | 73.78 Mn |
| Oct 31, 2024 | 75.98 Mn |
| Jul 31, 2024 | 72.41 Mn |
| Apr 30, 2024 | 75.29 Mn |
| Jan 31, 2024 | 64.84 Mn |
| Oct 31, 2023 | 63.87 Mn |
| Jul 31, 2023 | 64.45 Mn |
| Apr 30, 2023 | 63.53 Mn |
| Jan 31, 2023 | 58.09 Mn |
| Oct 31, 2022 | 62.35 Mn |
| Jul 31, 2022 | 47.30 Mn |
| Apr 30, 2022 | 53.93 Mn |
| Jan 31, 2022 | 42.11 Mn |
| Oct 31, 2021 | 43.28 Mn |
API Access
Elastic Accumulated 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=accumulated-expenses&ticker=ESTC&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "accumulated-expenses", "ticker": "ESTC", "period": "max", "api_key": "YOUR_API_KEY"}
data = requests.get(url, params=params).json()const res = await fetch("https://data.businessquant.com/historic?slug=accumulated-expenses&ticker=ESTC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();