Data Blocks: Hybrid OLTP and OLAP on Compressed Storage using both Vectorization and Compilation
Summary: Data Blocks: compressed columnar storage for cold data enabling high-performance hybrid OLTP/OLAP with minimal memory. Positional SMA narrows in-block scans; vectorized scans plus JIT pipelines yield fast OLTP and analytics on HyPer. (summarized by gpt-5-nano on Feb 09 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Harald Lang (Technical University of Munich)
- 2. Tobias Mühlbauer (Technical University of Munich)
- 3. Florian Funke (Snowflake; Technical University of Munich)
- 4. Peter Boncz (Centrum Wiskunde & Informatica; Technical University of Munich)
- 5. Thomas Neumann (Technical University of Munich)
- 6. Alfons Kemper (Technical University of Munich)
BibTeX Citation
@inproceedings{lang_sigmod16,
title = {{Data Blocks: Hybrid OLTP and OLAP on Compressed Storage using both Vectorization and Compilation}},
author = {Lang, Harald and Mühlbauer, Tobias and Funke, Florian and Boncz, Peter and Neumann, Thomas and Kemper, Alfons},
series = {{SIGMOD} '16},
booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
publisher = {Association for Computing Machinery},
doi = {10.1145/2882903.2882925},
url = {https://dl.acm.org/doi/10.1145/2882903.2882925},
year = {2016}
}Incoming Citations (Sorted by Pagerank)
Showing 50 of 53 citing papers.
Outgoing Citations (Sorted by Pagerank)
Showing 27 of 27 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
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