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Towards Unifying Query Interpretation and Compilation

Summary: Positions unifying vectorized interpretation (developer-friendly) and query compilation (better locality and runtime performance but high startup latency and system complexity) as key for modern execution engines. Discusses two fundamental barriers: startup overhead and engineering complexity. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
481
Venue
CIDR
Year
2023
Pagerank
5.1785299e-05
Overall Rank
10,008 | 31.34%
DOI
-

Incoming Non-self Citations Over Time

Authors

BibTeX Citation

@inproceedings{grulich_cidr23,
        address = {Amsterdam, Netherlands},
        series = {{CIDR} '23},
        title = {{Towards Unifying Query Interpretation and Compilation}},
        booktitle = {Proceedings of the {Conference} on {Innovative} {Data} {Systems} {Research}},
        author = {Grulich, Philipp M. and Lepping, Aljoscha and Nugroho, Dwi Prasetyo Adi and Del Monte, Bonaventura and Pandey, Varun and Zeuch, Steffen and Markl, Volker},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 3 of 3 citing papers.

Rank Citing Paper Year Venue Pagerank
7,108 Showcasing Data Management Challenges for Future IoT Applications with NebulaStream 2023 VLDB 5.7004611e-05
10,662 Data Chunk Compaction in Vectorized Execution 2025 SIGMOD 5.093636e-05
11,176 Fault Tolerance Placement in the Internet of Things 2024 SIGMOD 5.093636e-05
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Outgoing Citations (Sorted by Pagerank)

Showing 6 of 6 cited papers.

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

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