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My research centres around the making of data-intensive systems that are fast, cost-effective and energy-efficient, in the context of persistent memory, massively parallel processors and next-generation networks. I often step into related areas such as parallel programming and operating systems while solving problems in database systems. I also have interests in embedded and mobile systems. I am associated with the Systems Group and Data Science Research Group at SFU.

Graduate studies at SFU: Please take a look at the Prospective Students page first. See also the Data Science Research Group website for more opportunities.
SFU undergrads: We always work with undergrads on research projects. Feel free to contact me for opportunities. Taking my CMPT 454/740 and/or SoSy Capstone project is also a good way to get involved.

If you would like to schedule a meeting with me, please check my calendar.


  • May 3, 2021: A short version of our Dash paper that summarizes the key design principles of persistent hash tables is now available in SIGMOD Record 50(1) here, with a technical perspective by Prof. Ken Ross.
  • Apr 23, 2021: VLDB 2023 will come to Vancouver! I will serve as the local arrangements chair.
  • Feb 22, 2021: Our Trustworthy Data Science and AI seminar series will return with a great lineup of speakers in Spring 2021! Check out details here.
  • Feb 5, 2021: I will serve on the program committee for SIGMOD 2022.
  • Jan 28, 2021: I will serve as the (inaugural) artifact chair for VLDB 2021 (PVLDB Vol. 14).
  • Jan 18, 2021: I will serve on the program committee (review board) for VLDB 2022 (PVLDB Vol. 15).
  • Dec 19, 2020: Our Dash paper about scaling dynamic hash tables on persistent memory was selected for the 2021 ACM SIGMOD Research Highlight Award!
  • Dec 4, 2020: CoroBase recently covered by Hacker News.
  • Oct 16, 2020: New paper (CoroBase) about leveraging C++20 coroutines in storage engines to appear at VLDB 2021! Check out the preprint and code.
  • Oct 5, 2020: With Jian Pei and Jiannan Wang we are happy to announce a new (online) seminar series on trustworthy data science and AI starting Oct 16! Check out our Data Science Seminar website for details. All seminars are freely open to the public.
  • Jun 5, 2020: If you're working on (persistent memory) indexes and are looking for a unified, reproducible evaluation framework, check out our PiBench Online and its backend PiBench! We will demonstrate it at VLDB 2020.
  • May 30, 2020: I'll serve on the program committees for VLDB 2021 and SIGMOD 2021.
  • Mar 12, 2020: Our Dash paper about building scalable hash tables on persistent memory was accepted by VLDB 2020! Code available here, get it while it's hot.
  • Dec 18, 2019: Interested in knowing how database indexes perform on actual Intel Optane DC Persistent Memory after more than a decade of emulation based research? Check out our recent VLDB paper! We have also released an open-source tool (PiBench) for benchmarking persistent memory indexes.
  • Nov 30, 2019: I received the IEEE TCSC Award for Excellence in Scalable Computing (Early Career Researchers) for contributions to scalable data processing.

Recent Papers

Google Scholar

Scaling Dynamic Hash Tables on Real Persistent Memory. (invited) [Technical perspective] [Full paper at VLDB]
Baotong Lu, Xiangpeng Hao, Tianzheng Wang and Eric Lo.
SIGMOD Record 2021, Volume 50, Issue 1.

CoroBase: Coroutine-Oriented Main-Memory Database Engine. [code] [HackerNews discussion] [Talk at NWDS 2021]
Yongjun He, Jiacheng Lu and Tianzheng Wang.
VLDB 2021

Dash: Scalable Hashing on Persistent Memory. [abstract at NVMW 2021] [code]
Baotong Lu, Xiangpeng Hao, Tianzheng Wang and Eric Lo.
2021 ACM SIGMOD Research Highlight Award
VLDB 2020

Evaluating Persistent Memory Range Indexes. [PiBench code] [BzTree code]
Lucas Lersch, Xiangpeng Hao, Ismail Oukid, Tianzheng Wang and Thomas Willhalm.
VLDB 2020

PiBench Online: Interactive Benchmarking of Persistent Memory Indexes. [live system] [code] [demo video]
Xiangpeng Hao, Lucas Lersch, Tianzheng Wang and Ismail Oukid.
VLDB 2020 (Demo)

Parallelizing Filter-Verification based Exact Set Similarity Joins on Multicores. [code]
Fabian Fier, Tianzheng Wang, Erkang Zhu and Johann-Christoph Freytag.
Best Paper Award Candidate
SISAP 2020

Easy Lock-Free Programming in Non-Volatile Memory. [slides] [code]
Tianzheng Wang, Justin Levandoski and Per-Ake Larson.
Nominated for the Memorable Paper Award
NVMW 2019

DPI: The Data Processing Interface for Modern Networks.
Gustavo Alonso, Carsten Binnig, Ippokratis Pandis, Kenneth Salem, Jan Skrzypczak, Ryan Stutsman, Lasse Thostrup, Tianzheng Wang, Zeke Wang and Tobias Ziegler.
CIDR 2019

Easy Lock-Free Indexing in Non-Volatile Memory. [code]
Tianzheng Wang, Justin Levandoski and Per-Ake Larson.
ICDE 2018

Query Fresh: Log Shipping on Steroids. [slides] [poster] [code]
Tianzheng Wang, Ryan Johnson and Ippokratis Pandis.
VLDB 2018

Efficiently Making (almost) any Concurrency Control Mechanism Serializable. [preprint] [code]
Tianzheng Wang, Ryan Johnson, Alan Fekete and Ippokratis Pandis.
VLDBJ 2017, Volume 26, Issue 4.

Mostly-Optimistic Concurrency Control for Highly Contended Dynamic Workloads on 1000 Cores. [extended version] [slides] [poster] [code]
Tianzheng Wang and Hideaki Kimura.
VLDB 2017

Be My Guest - MCS Lock Now Welcomes Guests. [slides] [code]
Tianzheng Wang, Milind Chabbi and Hideaki Kimura.
PPoPP 2016

ERMIA: Fast Memory-Optimized Database System for Heterogeneous Workloads. [slides] [poster] [code]
Kangnyeon Kim, Tianzheng Wang, Ryan Johnson and Ippokratis Pandis.

Scalable Logging through Emerging Non-Volatile Memory. [abstract at NVMW 2015] [slides] [poster] [code]
Tianzheng Wang and Ryan Johnson.
VLDB 2014