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: 9.602292e-05
Overall Rank: 1,803 | 87.89%
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
5,720	Accelerating Python UDFs in Vectorized Query Execution	2022	CIDR	6.0159287e-05
5,929	Self-Organizing Data Containers	2022	CIDR	5.9411211e-05
6,086	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	5.8893767e-05
6,215	YeSQL: "You extend SQL" with Rich and Highly Performant User-Defined Functions in Relational Databases	2022	VLDB	5.8453061e-05
6,418	Containerized Execution of UDFs: An Experimental Evaluation	2022	VLDB	5.7899052e-05
6,747	Mitigating the Impedance Mismatch between Prediction Query Execution and Database Engine	2025	SIGMOD	5.6883491e-05
6,883	DAPHNE: An Open and Extensible System Infrastructure for Integrated Data Analysis Pipelines	2022	CIDR	5.6552024e-05
7,988	Efficient Execution of User-Defined Functions in SQL Queries	2023	VLDB	5.4105672e-05
8,159	Predicate Pushdown for Data Science Pipelines	2023	SIGMOD	5.3866275e-05
9,467	HyperBlocker: Accelerating Rule-based Blocking in Entity Resolution using GPUs	2025	VLDB	5.1709969e-05
9,483	Query Compilation Without Regrets	2024	SIGMOD	5.1686727e-05
9,596	The Key to Effective UDF Optimization: Before Inlining, First Perform Outlining	2025	VLDB	5.1543679e-05
9,663	BladeDISC: Optimizing Dynamic Shape Machine Learning Workloads via Compiler Approach	2023	SIGMOD	5.142891e-05
9,700	The UDFBench Benchmark for General-purpose UDF Queries	2025	VLDB	5.1372261e-05
10,051	YeSQL: Rich User-Defined Functions without the Overhead	2022	VLDB	5.0890428e-05
10,428	Automating Database-Native Function Code Synthesis with LLMs	2026	SIGMOD	4.9769913e-05
11,177	UDFBench: A Tool for Benchmarking UDF Queries on SQL Engines	2025	SIGMOD	4.9769913e-05
11,186	Approximating Opaque Top-k Queries	2025	SIGMOD	4.9769913e-05
11,734	Udon: Efficient Debugging of User-Defined Functions in Big Data Systems with Line-by-Line Control	2023	SIGMOD	4.9769913e-05
11,803	To UDFs and Beyond: Demonstration of a Fully Decomposed Data Processor for General Data Wrangling Tasks	2023	VLDB	4.9769913e-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	0.00056835296
23	Spark SQL: Relational Data Processing in Spark	2015	SIGMOD	0.00055384955
495	Building Efficient Query Engines in a High-Level Language	2014	VLDB	0.00017363171
605	Everything You Always Wanted to Know About Compiled and Vectorized Queries But Were Afraid to Ask	2018	VLDB	0.00015640305
1,445	An Architecture for Compiling UDF-centric Workflows	2015	VLDB	0.00010628379
1,722	A Sample-and-Clean Framework for Fast and Accurate Query Processing on Dirty Data	2014	SIGMOD	9.7921604e-05
1,744	How to Architect a Query Compiler	2016	SIGMOD	9.7332903e-05
1,933	Instant Loading for Main Memory Databases	2013	VLDB	9.3430609e-05
2,197	Opening the Black Boxes in Data Flow Optimization	2012	VLDB	8.8740089e-05
2,251	Evaluating End-to-End Optimization for Data Analytics Applications in Weld	2018	VLDB	8.750953e-05
2,420	How to Architect a Query Compiler, Revisited	2018	SIGMOD	8.4883426e-05
3,874	DBToaster: A SQL Compiler for High-Performance Delta Processing in Main-Memory Databases	2009	VLDB	6.9506516e-05
6,627	A Demonstration of DBWipes: Clean as You Query	2012	VLDB	5.7281668e-05

Semantically Similar Papers

#	Overall Rank	Paper	Year	Venue
1	12,291	The Best of Both Worlds: Big Data Programming with Both Productivity and Performance	2017	SIGMOD
2	2,055	tf.data: A Machine Learning Data Processing Framework	2021	VLDB
3	5,642	DataPrep.EDA: Task-Centric Exploratory Data Analysis for Statistical Modeling in Python	2021	SIGMOD
4	2,125	Tupleware: "Big" Data, Big Analytics, Small Clusters	2015	CIDR
5	1,193	Weld: A Common Runtime for High Performance Data Analytics	2017	CIDR
6	2,208	Magpie: Python at Speed and Scale using Cloud Backends	2021	CIDR
7	2,251	Evaluating End-to-End Optimization for Data Analytics Applications in Weld	2018	VLDB
8	5,720	Accelerating Python UDFs in Vectorized Query Execution	2022	CIDR
9	1,445	An Architecture for Compiling UDF-centric Workflows	2015	VLDB
10	10,052	Tuplex: Robust, Efficient Analytics When Python Rules	2019	VLDB