Kaltura (KLTR) Operating Expenses (2020 - 2026)
Kaltura (KLTR) recorded Operating Expenses of $35.31 million in Q2 2026, up 3.9% from $33.98 million a year earlier and up 5.9% from the prior quarter.
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Analysis
Kaltura (KLTR) Operating Expenses (2020 - 2026) Analysis & Trends
On a TTM basis, Kaltura's Operating Expenses came in at $132.99 million as of Jun 30, 2026, down 3.9% year-over-year; for FY2025, it came in at $132.63 million, down 7.4% from FY2024.
- Annual Operating Expenses has declined for three straight years, though with a five-year compound annual growth rate of 10.3% (FY2020 to FY2025).
- Across earlier years, Operating Expenses came in at $143.21 million in FY2024 (-5.1%), $150.89 million in FY2023 (-7.6%), $163.32 million in FY2022 (+20.6%) and $135.38 million in FY2021 (+66.6%).
- The Q2 2026 figure is the highest quarterly Operating Expenses since Q4 2024.
- On a year-over-year basis, Operating Expenses rose in 1 of the last eight quarters, with an average decline of 4.7%.
- Peak year-over-year performance for Operating Expenses in the last five years was growth of 74.2% in Q4 2021, against a decline of 12.6% in Q3 2023 at the low end.
- Per Business Quant, the preceding three quarters came in at $33.33 million (Q1 2026), $32.11 million (Q4 2025) and $32.23 million (Q3 2025).
Peer Set
Peer Comparison
| # | Company | Market Cap | Enterprise Value | Gross Profit (Qtr) | Opex (Qtr) |
|---|---|---|---|---|---|
| 1 | Alphabet | 4,164.76 Bn | 3,922.28 Bn | 73.85 Bn | 79.03 Bn |
| 2 | Meta Platforms | 1,823.40 Bn | 1,525.92 Bn | 49.47 Bn | 42.03 Bn |
| 3 | Netflix | 288.27 Bn | 248.47 Bn | 6.52 Bn | 1.51 Bn |
| 4 | Alibaba Group Holding | 252.72 Bn | 70.58 Bn | 15.11 Bn | -5.17 Bn |
| 5 | Shopify | 186.52 Bn | 163.71 Bn | 1.71 Bn | 1.22 Bn |
| 6 | Uber Technologies | 139.11 Bn | 111.09 Bn | 6.38 Bn | 12.30 Bn |
| 7 | Booking Holdings | 123.13 Bn | 56.18 Bn | - | 4.85 Bn |
| 8 | PDD Holdings | 111.72 Bn | -140.21 Bn | 9.45 Bn | -5.39 Bn |
| 9 | AppLovin | 103.35 Bn | 93.38 Bn | 1.70 Bn | 429.41 Mn |
| 10 | Kaltura | 197.28 Mn | -19.90 Mn | 34.54 Mn | 35.31 Mn |
Historic Data
Download Data
Historic Data
| Date | Value |
|---|---|
| Jun 30, 2026 | 35.31 Mn |
| Mar 31, 2026 | 33.33 Mn |
| Dec 31, 2025 | 32.11 Mn |
| Sep 30, 2025 | 32.23 Mn |
| Jun 30, 2025 | 33.98 Mn |
| Mar 31, 2025 | 34.31 Mn |
| Dec 31, 2024 | 36.07 Mn |
| Sep 30, 2024 | 34.01 Mn |
| Jun 30, 2024 | 37.23 Mn |
| Mar 31, 2024 | 35.90 Mn |
| Dec 31, 2023 | 37.47 Mn |
| Sep 30, 2023 | 36.01 Mn |
| Jun 30, 2023 | 38.16 Mn |
| Mar 31, 2023 | 39.25 Mn |
| Dec 31, 2022 | 38.97 Mn |
| Sep 30, 2022 | 41.23 Mn |
| Jun 30, 2022 | 42.20 Mn |
| Mar 31, 2022 | 40.93 Mn |
| Dec 31, 2021 | 39.20 Mn |
| Sep 30, 2021 | 33.69 Mn |
API Access
Kaltura 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=KLTR&period=max&api_key=YOUR_API_KEYimport requests
url = "https://data.businessquant.com/historic"
params = {"slug": "operating-expenses", "ticker": "KLTR", "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=KLTR&period=max&api_key=YOUR_API_KEY");
const data = await res.json();