DBScholar

Back to papers

Big Data Analytic Toolkit: A general-purpose, modular, and heterogeneous acceleration toolkit for data analytical engines

Summary: BDTK: an open-source C++ toolkit of lightweight, modular, interoperable components to bring query compilation (vectorized execution and data-centric codegen) and heterogeneous hardware accelerators to analytical engines. Reduces engineering cost to adopt and integrate acceleration across diverse engines. (summarized by gpt-5-mini on Feb 09 2026)

Paper ID
13388
Venue
VLDB
Year
2023
Pagerank
5.093636e-05
Overall Rank
11,468 | 21.32%
DOI
10.14778/3611540.3611558

Incoming Non-self Citations Over Time

No non-self incoming citations found for this paper in this database.

Authors

BibTeX Citation

@article{li_vldb23,
        title = {{Big Data Analytic Toolkit: A general-purpose, modular, and heterogeneous acceleration toolkit for data analytical engines}},
        author = {Li, Jiang and Xie, Qi and Ma, Yan and Ma, Jian and Ji, Kunshang and Zhang, Yizhong and Zhang, Chaojun and Chen, Yixiu and Wu, Gangsheng and Zhang, Jie and Yang, Kaidi and He, Xinyi and Shen, Qiuyang and Tao, Yanting and Zhao, Haiwei and Jiao, Penghui and Zhu, Chengfei and Qian, David and Xu, Cheng},
        journal = {PVLDB},
        series = {{VLDB} '23},
        volume = {16},
        number = {12},
        pages = {3702--3714},
        doi = {10.14778/3611540.3611558},
        url = {https://doi.org/10.14778/3611540.3611558},
        year = {2023}
}

Incoming Citations (Sorted by Pagerank)

Showing 0 of 0 citing papers.

Rank Citing Paper Year Venue Pagerank
Previous Page 1 / 1 Next

Outgoing Citations (Sorted by Pagerank)

Showing 12 of 12 cited papers.

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

Rank Cited Paper Year Venue Pagerank
14 MonetDB/X100: Hyper-Pipelining Query Execution 2005 CIDR 0.0006312782
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
649 Everything You Always Wanted to Know About Compiled and Vectorized Queries But Were Afraid to Ask 2018 VLDB 0.00015320656
818 Amazon Redshift Re-invented 2022 SIGMOD 0.00013822916
1,379 Relaxed Operator Fusion for In-Memory Databases: Making Compilation, Vectorization, and Prefetching Work Together At Last 2018 VLDB 0.00010970894
1,757 Velox: Meta's Unified Execution Engine 2022 VLDB 9.8166984e-05
1,797 How to Architect a Query Compiler 2016 SIGMOD 9.7368925e-05
1,824 Photon: A Fast Query Engine for Lakehouse Systems 2022 SIGMOD 9.6734544e-05
4,215 Designing an Open Framework for Query Optimization and Compilation 2022 VLDB 6.8275676e-05
5,376 Evolution of a Compiling Query Engine 2021 VLDB 6.2415397e-05
7,604 Hardware Acceleration of Compression and Encryption in SAP HANA 2022 VLDB 5.5853563e-05
Previous Page 1 / 1 Next

Semantically Similar Papers

# Overall Rank Paper Year Venue
1 8,053 Maximus: A Modular Accelerated Query Engine for Data Analytics on Heterogeneous Systems 2025 SIGMOD
2 10,580 GPU Acceleration of SQL Analytics on Compressed Data 2026 VLDB
3 3,682 In-RDBMS Hardware Acceleration of Advanced Analytics 2018 VLDB
4 10,541 Scalable GPU Acceleration of Scalar Functions in Analytical Databases: Compilation, Benchmarking, and Optimization 2026 VLDB
5 1,442 An Architecture for Compiling UDF-centric Workflows 2015 VLDB
6 13,575 From Data to Insights @ Bare Metal Speed 2015 SIGMOD
7 2,594 Big Data Analytics with Datalog Queries on Spark 2016 SIGMOD
8 3,791 Hardware-conscious Query Processing in GPU-accelerated Analytical Engines 2019 CIDR
9 8,636 Adaptive Code Generation for Data-Intensive Analytics 2021 VLDB
10 8,104 Enabling Transparent Acceleration of Big Data Frameworks Using Heterogeneous Hardware 2022 VLDB