About Me

I recently completed my PhD at Stanford and am now co-founding DBOS, Inc. to make it easy for developers to build scalable, reliable, and secure applications!

In graduate school, I studied computer science (particularly databases and systems research) and was advised by Matei Zaharia and Peter Bailis. In my PhD, I worked on the DBMS-oriented Operating System (DBOS) academic project (CIDR 2022, VLDB 2022), which our startup is now commercializing. I was particularly involved in Epoxy (VLDB 2023) and Apiary (arXiv). Other projects I have worked on include Data-Parallel Actors (NSDI 2022), POP (SOSP 2021), Willump (MLSys 2020, VLDB 2020), MacroBase (Best of VLDB 2019) and Arachne (OSDI 2018). I did my undergrad at Harvard, where I worked with Margo Seltzer on my senior thesis and Alexander Rush on predicting congressional voting records from bill text (EMNLP 2016).

Blog Posts

Contact Details

Peter Kraft
peter.kraft [at] dbos.dev

Publications

* Denotes Equal Contribution

Epoxy: ACID Transactions Across Diverse Data Stores
Peter Kraft, Qian Li, Xinjing Zhou, Peter Bailis, Michael Stonebraker, Xiangyao Yu, Matei Zaharia
International Conference on Very Large Data Bases (VLDB) 2023.

R3: Record-Replay-Retroaction for Database-Backed Applications.
Qian Li, Peter Kraft, Michael Cafarella, Çağatay Demiralp, Goetz Graefe, Christos Kozyrakis, Michael Stonebraker, Lalith Suresh, Xiangyao Yu, Matei Zaharia.
International Conference on Very Large Data Bases (VLDB) 2023.

Parallelism-Optimizing Data Placement for Faster Data-Parallel Computations.
Nirvik Baruah, Peter Kraft, Fiodar Kazhamiaka, Peter Bailis, Matei Zaharia.
International Conference on Very Large Data Bases (VLDB) 2023.

Analyzing and Comparing Lakehouse Storage Systems.
Paras Jain*, Peter Kraft*, Conor Power*, Tathagata Das, Ion Stoica, Matei Zaharia.
Conference on Innovative Data Systems Research (CIDR) 2023.

Transactions Make Debugging Easy.
Qian Li, Peter Kraft, Michael Cafarella, Çağatay Demiralp, Goetz Graefe, Christos Kozyrakis, Michael Stonebraker, Lalith Suresh, Matei Zaharia.
Conference on Innovative Data Systems Research (CIDR) 2023.

Apiary: A DBMS-Backed Transactional Function-as-a-Service Framework.
Peter Kraft*, Qian Li*, Kostis Kaffes, Athinagoras Skiadopoulos, Deeptaanshu Kumar, Danny Cho, Jason Li, Robert Redmond, Nathan Weckwerth, Brian Xia, Peter Bailis, Michael Cafarella, Goetz Graefe, Jeremy Kepner, Christos Kozyrakis, Michael Stonebraker, Lalith Suresh, Xiangyao Yu, Matei Zaharia.
arXiv Preprint.

Machine Learning with DBOS.
Robert Redmond, Nathan W. Weckwerth, Brian S. Xia, Qian Li, Peter Kraft, Deeptaanshu Kumar, Çağatay Demiralp, Michael Stonebraker.
International Workshop on Applied AI for Database Systems (AIDB) 2022

Data-Parallel Actors: A Programming Model for Scalable Query Serving Systems.
Peter Kraft, Fiodar Kazhamiaka, Peter Bailis, Matei Zaharia.
Symposium on Networked Systems Design and Implementation (NSDI) 2022.

A Progress Report on DBOS: A DBMS-Oriented Operating System.
Qian Li*, Peter Kraft*, Kostis Kaffes*, Athinagoras Skiadopoulos, Deeptaanshu Kumar, Jason Li, Michael Cafarella, Goetz Graefe, Jeremy Kepner, Christos Kozyrakis, Michael Stonebraker, Lalith Suresh, Matei Zaharia.
Conference on Innovative Data Systems Research (CIDR) 2022.

DBOS: A DBMS-Oriented Operating System.
Athinagoras Skiadopoulos*, Qian Li*, Peter Kraft*, Kostis Kaffes*, Daniel Hong, Shana Matthew, David Bestor, Michael Cafarella, Vijay Gadepally, Goetz Graefe, Jeremy Kepner, Christos Kozyrakis, Tim Kraska, Michael Stonebraker, Lalith Suresh, Matei Zaharia.
International Conference on Very Large Data Bases (VLDB) 2022.

Solving Large-Scale Granular Resource Allocation Problems Efficiently with POP.
Deepak Narayanan, Fiodar Kazhamiaka, Firas Abuzaid, Peter Kraft, Akshay Agrawal, Srikanth Kandula, Stephen Boyd, Matei Zaharia.
Symposium on Operating Systems Principles (SOSP) 2021.

Data Governance in a Database Operating System (DBOS).
Deeptaanshu Kumar, Qian Li, Jason Li, Peter Kraft, Athinagoras Skiadopoulos, Lalith Suresh, Michael Cafarella, Michael Stonebraker.
VLDB Workshop on Polystore Systems (Poly) 2021.

DIFF: A Relational Interface for Large-Scale Data Explanation.
Firas Abuzaid, Peter Kraft, Sahaana Suri, Edward Gan, Eric Xu, Atul Shenoy, Asvin Ananthanarayan, John Sheu, Erik Meijer, Xi Wu, Jeff Naughton, Peter Bailis, Matei Zaharia.
The VLDB Journal, 2020. "Best of VLDB 2019" Special Issue.

A Demonstration of Willump: A Statistically-Aware End-to-end Optimizer for Machine Learning Inference.
Peter Kraft, Daniel Kang, Deepak Narayanan, Shoumik Palkar, Peter Bailis, Matei Zaharia.
International Conference on Very Large Data Bases (VLDB) 2020.

Willump: A Statistically-Aware End-to-end Optimizer for Machine Learning Inference.
Peter Kraft, Daniel Kang, Deepak Narayanan, Shoumik Palkar, Peter Bailis, Matei Zaharia.
Conference on Machine Learning and Systems (MLSys) 2020.

DIFF: A Relational Interface for Large-Scale Data Explanation.
Firas Abuzaid, Peter Kraft, Sahaana Suri, Edward Gan, Eric Xu, Atul Shenoy, Asvin Ananthanarayan, John Sheu, Erik Meijer, Xi Wu, Jeff Naughton, Peter Bailis, Matei Zaharia.
International Conference on Very Large Data Bases (VLDB) 2019.

Arachne: Core-Aware Thread Management.
Henry Qin, Qian Li, Jacqueline Speiser, Peter Kraft, John Ousterhout.
Symposium on Operating Systems Design and Implementation (OSDI) 2018.

Automatically Scalable Computation That Is More Scalable and Automatic.
Peter Kraft.
Harvard University Senior Thesis. 2017.

Improving Supreme Court Forecasting Using Boosted Decision Trees.
Aaron Kaufman, Peter Kraft, Maya Sen.
Political Analysis. 2019.

An Embedding Model For Predicting Roll-Call Votes.
Peter Kraft, Hirsh Jain, Alexander Rush.
Empirical Methods for Natural Language Processing (EMNLP) 2016.