Elastic (ESTC) Change in Accured Expenses (2018 - 2026)
Elastic's Change in Accured Expenses came in at -$19.49 million for fiscal Q1 2027 (quarter ended Jul 31, 2026), compared with -$14.89 million a year earlier.
Elastic (ESTC) Change in Accured Expenses (2018 - 2026) Analysis & Trends
Over the trailing twelve months to Jul 31, 2026, Elastic reported Change in Accured Expenses of $20.44 million, up 60.4% year-over-year; for FY2026 (ended Apr 30, 2026), it came in at $25.04 million, up 154.4% from FY2025.
- Change in Accured Expenses carries a five-year compound annual growth rate of 25.3% (FY2021 to FY2026).
- Going back by fiscal year, Change in Accured Expenses was $9.85 million in FY2025 (-45.7%), $18.14 million in FY2024 (+118.0%), $8.32 million in FY2023 (-69.4%) and $27.19 million in FY2022 (+235.0%).
- The fiscal Q1 2027 figure represents the lowest quarterly Change in Accured Expenses in data going back to fiscal Q3 2018.
- The fastest year-over-year change in Change in Accured Expenses over five years came in fiscal Q2 2022 (growth of 195.8%), and the weakest in fiscal Q2 2023 (a decline of 40.6%).
- Business Quant data shows ESTC's Change in Accured Expenses at $22.31 million (Q4 2026), -$5.4 million (Q3 2026) and $23.03 million (Q2 2026) in the three fiscal quarters before Q1 2027.
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Change Accured Exp. (Qtr) |
|---|---|---|---|---|---|
| 1 | Palo Alto Networks | 328.64 Bn | 313.71 Bn | 2.30 Bn | 369.00 Mn |
| 2 | CrowdStrike Holdings | 276.50 Bn | 256.94 Bn | 1.10 Bn | 72.38 Mn |
| 3 | Fortinet | 132.74 Bn | 118.67 Bn | 1.64 Bn | 75.10 Mn |
| 4 | Snowflake | 120.19 Bn | 107.50 Bn | 1.04 Bn | 108.85 Mn |
| 5 | Datadog | 99.51 Bn | 81.15 Bn | 881.34 Mn | 6.98 Mn |
| 6 | Okta | 35.35 Bn | 25.44 Bn | 641.00 Mn | -2.00 Mn |
| 7 | Axon Enterprise | 33.58 Bn | 28.10 Bn | 546.45 Mn | 256.58 Mn |
| 8 | Zscaler | 32.06 Bn | 18.18 Bn | - | - |
| 9 | MongoDB | 28.84 Bn | 19.30 Bn | 569.77 Mn | 43.09 Mn |
| 10 | Elastic | 9.88 Bn | 4.40 Bn | 356.19 Mn | -19.49 Mn |
Historic Data
| Date | Value |
|---|---|
| Jul 31, 2026 | -19.49 Mn |
| Apr 30, 2026 | 22.31 Mn |
| Jan 31, 2026 | -5.40 Mn |
| Oct 31, 2025 | 23.03 Mn |
| Jul 31, 2025 | -14.89 Mn |
| Apr 30, 2025 | 22.65 Mn |
| Jan 31, 2025 | 8.68 Mn |
| Oct 31, 2024 | -3.69 Mn |
| Jul 31, 2024 | -17.79 Mn |
| Apr 30, 2024 | 16.64 Mn |
| Jan 31, 2024 | 12.28 Mn |
| Oct 31, 2023 | -6.89 Mn |
| Jul 31, 2023 | -3.89 Mn |
| Apr 30, 2023 | 14.60 Mn |
| Jan 31, 2023 | -325,000.00 |
| Oct 31, 2022 | 10.79 Mn |
| Jul 31, 2022 | -16.74 Mn |
| Apr 30, 2022 | 9.65 Mn |
| Jan 31, 2022 | 820,000.00 |
| Oct 31, 2021 | 18.17 Mn |
Elastic Change in Accured 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=change-in-accured-expenses&ticker=ESTC&period=max&api_key=YOUR_API_KEY
import requests
url = "https://data.businessquant.com/historic"
params = {"slug": "change-in-accured-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=change-in-accured-expenses&ticker=ESTC&period=max&api_key=YOUR_API_KEY");
const data = await res.json();