Vectorized Query Execution Patents: Who Leads, Where Gaps Are 2026
Vectorized Query Execution Patents: Concentration, Trends and Open Ground
One filer dominates. the leading assignee alone accounts for 2,366 of the 3,183 records in scope, with the top 5 combined reaching 92.1%. Filings rose from 71 in 2017 to a peak of 662 in 2021, then declined to 321 by 2024 (-52% over that three-year span). 2025 and 2026 figures are still incomplete due to publication lag and should not be read as a continued decline.
- 1NVIDIA CORP2,366
- 2INTEL CORP422
- 3ORACLE INT CORP65
- 4MELLANOX TECHNOLOGIES LTD(IL)42
- 5INTERNATIONAL BUSINESS MACHINE CORPORATION36
See the full vectorized query execution analysis in Eureka
- The complete ranking, not just the top five
- Every IPC branch with its share of the corpus
- The most-cited records, and where claim space is still thin
Common questions about vectorized query execution patents
Who holds the most patents in vectorized query execution?
One assignee holds a clear majority of the records in this dataset, with 2,366 of 3,183 records in scope — well ahead of the rest of the ranked field. The top five assignees combined account for 92.1% of all records, and by tenth place volume has already dropped to 12 records. This means freedom-to-operate analysis in this space should start with the leading filer’s claim scope before looking at the long tail.
Is patent filing for vectorized query execution growing or shrinking?
Filing peaked in 2021 at 662 records and fell to 321 by 2024, a -52% change over that span, the last period that can be treated as complete. It is not accurate to describe 2025-2026 as a continued decline, because publication typically lags filing by around 18 months and those years are still filling in. The honest read is that the field passed its filing peak in 2021 and has settled to a lower, but not yet fully known, pace.
What technology areas overlap most with vectorized query execution patents?
G06F (electric digital data processing) appears in 50.0% of the 3,183 records, and G06N (computing based on AI models) appears in 30.1%, showing heavy overlap with machine-learning workloads rather than database engines alone. G06T (image data processing) at 28.7% adds a further graphics-adjacent overlap. Narrower classes like H04L (digital transmission, 3.2%) and H04N (pictorial communication, 3.4%) carry much lower claim density and may represent comparatively open ground.
Disclaimer. This analysis is based on Patsnap Eureka data drawn from a limited snapshot of global patent records and is provided for general information and reference only. Patent data carries inherent limitations — recent filings are under-counted because of publication lag, counts may be on a record or family basis, classification and applicant-name data may contain errors or duplicates, and the underlying search query defines the scope shown — so the analysis may be incomplete or inaccurate and may not reflect the full technology landscape.
Nothing here is an exhaustive prior-art, novelty, freedom-to-operate or validity search, nor does it constitute legal, financial or professional advice, and it should not be relied upon as such. Verify independently and review with qualified patent and legal professionals before acting on it.
Method: Filing trend and technology composition. Derived from a Patsnap search on Vectorized Query Execution covering 2015–2026, data cut-off 2026-07-31. Counts reflect published records only and shift as new filings publish. Every share divides by all records in scope. Data: Patsnap Eureka. See the full landscape report.