UmbraPerf - Profiling Results Tailored for DBMS Developers

Summary: UmbraPerf maps sampled profiling data to DBMS abstractions—from query-plan operators to generated code—by combining samples with metadata for code‑generating DBMSs. Its interactive frontend provides multi-level visualizations to drill from operator hotspots to instructions. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID: 14325
Venue: VLDB
Year: 2025
Pagerank: -
Overall Rank: 13,336 | 8.51%
DOI: 10.14778/3750601.3750654

Incoming Non-self Citations Over Time

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Authors

1. Alexander Beischl (Technical University of Munich)
2. Thomas Neumann (Technical University of Munich)

BibTeX Citation

@article{beischl_vldb25,
        title = {{UmbraPerf - Profiling Results Tailored for DBMS Developers}},
        author = {Beischl, Alexander and Neumann, Thomas},
        journal = {PVLDB},
        series = {{VLDB} '25},
        volume = {18},
        number = {12},
        pages = {5291--5294},
        doi = {10.14778/3750601.3750654},
        url = {https://doi.org/10.14778/3750601.3750654},
        year = {2025}
}

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank

Outgoing Citations (Sorted by Pagerank)

Showing 3 of 3 cited papers.

Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.

Rank	Cited Paper	Year	Venue	Pagerank
23	Efficiently Compiling Efficient Query Plans for Modern Hardware	2011	VLDB	0.00054886415
422	Umbra: A Disk-Based System with In-Memory Performance	2020	CIDR	0.00018732744
7,787	A Practical Approach to Groupjoin and Nested Aggregates	2021	VLDB	5.5449593e-05

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