Voodoo - A Vector Algebra for Portable Database Performance on Modern Hardware
Summary: Voodoo is a declarative, vector-oriented intermediate algebra that captures cache, SIMD, and parallelism abstractions while generating highly tuned CPU/GPU code. Its novel control vectors enable portable performance, matching state-of-the-art in-memory engines via a MonetDB backend. (summarized by gpt-5.6-luna on Jul 24 2026)
Incoming Non-self Citations Over Time
Authors
- 1. Holger Pirk (Massachusetts Institute of Technology)
- 2. Oscar Moll (Massachusetts Institute of Technology)
- 3. Matei Zaharia (Massachusetts Institute of Technology)
- 4. Sam Madden (Massachusetts Institute of Technology)
BibTeX Citation
@article{pirk_vldb16,
title = {{Voodoo - A Vector Algebra for Portable Database Performance on Modern Hardware}},
author = {Pirk, Holger and Moll, Oscar and Zaharia, Matei and Madden, Sam},
journal = {PVLDB},
series = {{VLDB} '16},
volume = {9},
number = {14},
pages = {1707--1718},
doi = {10.14778/3007328.3007336},
url = {https://doi.org/10.14778/3007328.3007336},
year = {2016}
}Incoming Citations (Sorted by Pagerank)
Showing 37 of 37 citing papers.
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Outgoing Citations (Sorted by Pagerank)
Showing 8 of 8 cited papers.
Citations counted here include only citations to other VLDB/SIGMOD/CIDR/PODS papers in this database.
| Rank | Cited Paper | Year | Venue | Pagerank |
|---|---|---|---|---|
| 21 | Efficiently Compiling Efficient Query Plans for Modern Hardware | 2011 | VLDB | 0.00056835296 |
| 163 | DB2 with BLU Acceleration: So Much More than Just a Column Store | 2013 | VLDB | 0.00027480091 |
| 495 | Building Efficient Query Engines in a High-Level Language | 2014 | VLDB | 0.00017363171 |
| 627 | Rethinking SIMD Vectorization for In-Memory Databases | 2015 | SIGMOD | 0.00015454197 |
| 857 | Hardware-Oblivious Parallelism for In-Memory Column-Stores | 2013 | VLDB | 0.00013422539 |
| 2,125 | Tupleware: "Big" Data, Big Analytics, Small Clusters | 2015 | CIDR | 9.0017828e-05 |
| 3,142 | Evita Raced: Metacompilation for Declarative Networks | 2008 | VLDB | 7.595954e-05 |
| 5,663 | Enabling Incremental Query Re-Optimization | 2016 | SIGMOD | 6.0448133e-05 |
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| # | Overall Rank | Paper | Year | Venue |
|---|---|---|---|---|
| 1 | 10,196 | Towards Unifying Query Interpretation and Compilation | 2023 | CIDR |
| 2 | 8,602 | A Case for Graphics-driven Query Processing | 2023 | VLDB |
| 3 | 5,545 | Charting the Design Space of Query Execution using VOILA | 2021 | VLDB |
| 4 | 4,540 | OmniDB: Towards Portable and Efficient Query Processing on Parallel CPU/GPU Architectures | 2013 | VLDB |
| 5 | 21 | Efficiently Compiling Efficient Query Plans for Modern Hardware | 2011 | VLDB |
| 6 | 7,735 | Hardware-Oblivious SIMD Parallelism for In-Memory Column-Stores | 2020 | CIDR |
| 7 | 605 | Everything You Always Wanted to Know About Compiled and Vectorized Queries But Were Afraid to Ask | 2018 | VLDB |
| 8 | 8,605 | doppioDB: A Hardware Accelerated Database | 2017 | SIGMOD |
| 9 | 627 | Rethinking SIMD Vectorization for In-Memory Databases | 2015 | SIGMOD |
| 10 | 857 | Hardware-Oblivious Parallelism for In-Memory Column-Stores | 2013 | VLDB |