Contact Info

  • Office: GHC 9019
  • Office Hours: Mondays @ 12:00
  • Email: pavlo@cs.cmu.edu
  • Twitter: @andy_pavlo
  • GitHub: apavlo

Upcoming Talks

  • Jun 23 — DAMON Panel
  • Jun 26 — SIGMOD 2014
  • Jul 2 — Leap@CMU
  • Past Schedule

    Project Links

    I am an Assistant Professor in the Computer Science Department at Carnegie Mellon University. My research interest is in database management systems, specifically main memory systems, non-relational systems (NoSQL), transaction processing systems (NewSQL), and large-scale data analytics. At CMU, I am a member of the Database Group and the Parallel Data Laboratory. My work is also in collaboration with the Intel Science and Technology Center for Big Data.

    Current Students:

    Teaching:

    Research Projects:

    H-Store

    The goal of the H-Store project is to investigate how recent architectural and application trends affect the performance of on-line transaction processing databases and to study what performance benefits are possible with a complete redesign of OLTP systems. [More Info]

    S-Store

    We are developing an in-memory, distributed stream processing engine that is integrated with a front-end, OLTP database system. The goal of the S-Store project is to deploy continous query workloads in the front-end system without degrading the performance of the regular OLTP workload. We are also exploring the meaning of transactional semantics (e.g., consistency, isolation) in a streaming environment.

    N-Store

    The onset of non-volatile memory (NVM) devices will require us to rethink the dichotomy between memory and durable storage. These devices promise to overcome the disparity between processor performance and DRAM storage capacity limits that encumber data-centric applications. As part of the Big Data ISTC, we are studying NVMs to understand their performance characteristics in the context of big data systems and build the groundwork for new DBMS architectures.

    OLTP-Bench

    OLTP-Bench is an extensible "batteries included" DBMS benchmarking testbed with over a dozen workloads that all differ in complexity and system demands. The key contributions of the project are its ease of use and extensibility, support for tight control of transaction mixtures, request rates, and access distributions over time, as well as the ability to support all major DBMSs. [More Info]

    Professional Activities: