Tuplex: Data Science in Python at Native Code Speed

Summary: Tuplex JIT-compiles Python UDFs into end-to-end native code for data pipelines. It uses a dual-mode execution model: a fast path for the common case with exception paths for failures, yielding up to 91x speedups over Spark/Dask and near hand-tuned C++ performance. (summarized by gpt-5-nano on Feb 09 2026)

Paper ID: h9c34eb13be105218
Venue: SIGMOD
Year: 2021
Pagerank: 9.5747668e-05
Overall Rank: 1,812 | 87.86%
DOI: 10.1145/3448016.3457244

Incoming Non-self Citations Over Time

Authors

1. Leonhard Spiegelberg
2. Rahul Yesantharao (Brown University)
3. Malte Schwarzkopf (Massachusetts Institute of Technology)
4. Tim Kraska (Massachusetts Institute of Technology)

BibTeX Citation

@inproceedings{spiegelberg_sigmod21,
        title = {{Tuplex: Data Science in Python at Native Code Speed}},
        author = {Spiegelberg, Leonhard and Yesantharao, Rahul and Schwarzkopf, Malte and Kraska, Tim},
        series = {{SIGMOD} '21},
        booktitle = {Proceedings of the {ACM} {SIGMOD} International Conference on Management of Data},
        publisher = {Association for Computing Machinery},
        doi = {10.1145/3448016.3457244},
        url = {https://dl.acm.org/doi/10.1145/3448016.3457244},
        year = {2021}
}

Incoming Citations (Sorted by Pagerank)

Showing 20 of 20 citing papers.

Rank	Citing Paper	Year	Venue	Pagerank
5,723	Accelerating Python UDFs in Vectorized Query Execution	2022	CIDR	5.9993122e-05
5,935	Self-Organizing Data Containers	2022	CIDR	5.9251217e-05
6,100	Dear User-Defined Functions, Inlining isn't working out so great for us. Let's try batching to make our relationship work. Sincerely, SQL	2024	CIDR	5.8699028e-05
6,218	YeSQL: "You extend SQL" with Rich and Highly Performant User-Defined Functions in Relational Databases	2022	VLDB	5.8292066e-05
6,428	Containerized Execution of UDFs: An Experimental Evaluation	2022	VLDB	5.7709339e-05
6,765	Mitigating the Impedance Mismatch between Prediction Query Execution and Database Engine	2025	SIGMOD	5.6695399e-05
6,902	DAPHNE: An Open and Extensible System Infrastructure for Integrated Data Analysis Pipelines	2022	CIDR	5.6365602e-05
8,002	Efficient Execution of User-Defined Functions in SQL Queries	2023	VLDB	5.3927693e-05
8,176	Predicate Pushdown for Data Science Pipelines	2023	SIGMOD	5.3688159e-05
8,635	The Key to Effective UDF Optimization: Before Inlining, First Perform Outlining	2025	VLDB	5.2832224e-05
9,475	HyperBlocker: Accelerating Rule-based Blocking in Entity Resolution using GPUs	2025	VLDB	5.157794e-05
9,512	Query Compilation Without Regrets	2024	SIGMOD	5.1515819e-05
9,691	BladeDISC: Optimizing Dynamic Shape Machine Learning Workloads via Compiler Approach	2023	SIGMOD	5.1258854e-05
9,729	The UDFBench Benchmark for General-purpose UDF Queries	2025	VLDB	5.1202393e-05
10,060	YeSQL: Rich User-Defined Functions without the Overhead	2022	VLDB	5.0753869e-05
10,494	Automating Database-Native Function Code Synthesis with LLMs	2026	SIGMOD	4.9605343e-05
11,236	UDFBench: A Tool for Benchmarking UDF Queries on SQL Engines	2025	SIGMOD	4.9605343e-05
11,245	Approximating Opaque Top-k Queries	2025	SIGMOD	4.9605343e-05
11,778	Udon: Efficient Debugging of User-Defined Functions in Big Data Systems with Line-by-Line Control	2023	SIGMOD	4.9605343e-05
11,847	To UDFs and Beyond: Demonstration of a Fully Decomposed Data Processor for General Data Wrangling Tasks	2023	VLDB	4.9605343e-05

Outgoing Citations (Sorted by Pagerank)

Showing 13 of 13 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	0.00056737487
23	Spark SQL: Relational Data Processing in Spark	2015	SIGMOD	0.00055523999
498	Building Efficient Query Engines in a High-Level Language	2014	VLDB	0.00017323427
606	Everything You Always Wanted to Know About Compiled and Vectorized Queries But Were Afraid to Ask	2018	VLDB	0.00015609823
1,449	An Architecture for Compiling UDF-centric Workflows	2015	VLDB	0.00010597074
1,721	A Sample-and-Clean Framework for Fast and Accurate Query Processing on Dirty Data	2014	SIGMOD	9.7821782e-05
1,756	How to Architect a Query Compiler	2016	SIGMOD	9.7053947e-05
1,942	Instant Loading for Main Memory Databases	2013	VLDB	9.3133693e-05
2,124	Opening the Black Boxes in Data Flow Optimization	2012	VLDB	8.9915327e-05
2,258	Evaluating End-to-End Optimization for Data Analytics Applications in Weld	2018	VLDB	8.7387151e-05
2,433	How to Architect a Query Compiler, Revisited	2018	SIGMOD	8.4614165e-05
3,886	DBToaster: A SQL Compiler for High-Performance Delta Processing in Main-Memory Databases	2009	VLDB	6.9280841e-05
6,636	A Demonstration of DBWipes: Clean as You Query	2012	VLDB	5.7094244e-05

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