Mainlining Databases: Supporting Fast Transactional Workloads on Universal Columnar Data File Formats
Summary: In-memory DBMS storage emits universal columnar blocks (Apache Arrow) tailored to data usage, reducing OLTP-analytic data movement. Relaxed update formats with lightweight transforms to read-optimized layouts on cold data and fast Arrow exports in NoisePage yield OLTP parity and large export speedups. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Tianyu Li (Massachusetts Institute of Technology)
- 2. Matthew Butrovich (Carnegie Mellon University)
- 3. Amadou Ngom (Massachusetts Institute of Technology)
- 4. Wan Shen Lim (Carnegie Mellon University)
- 5. Wes McKinney (Ursa Labs)
- 6. Andrew Pavlo (Carnegie Mellon University)
BibTeX Citation
@article{li_vldb21,
title = {{Mainlining Databases: Supporting Fast Transactional Workloads on Universal Columnar Data File Formats}},
author = {Li, Tianyu and Butrovich, Matthew and Ngom, Amadou and Lim, Wan Shen and McKinney, Wes and Pavlo, Andrew},
journal = {PVLDB},
series = {{VLDB} '21},
volume = {14},
number = {4},
pages = {534--546},
doi = {10.14778/3436905.3436913},
url = {https://doi.org/10.14778/3436905.3436913},
year = {2021}
}
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