I am a senior principal researcher in the database group at Microsoft Research. I am interested in creating technologies to perform real-time and offline big and raw data processing, as well as resilient state management for cloud and edge applications. My work on stream processing first shipped commercially in 2010 with Microsoft SQL Server, as the StreamInsight engine. My recent project, Trill, is an analytics engine that is widely used at Microsoft, for example, in the Bing advertising platform and as part of the public-facing Azure Stream Analytics service (see MSR’s blog post for more information). Recently, I built FASTER, a new high-performance concurrent key-value store that supports larger-than-memory data and is optimized for the hot working set.

Learn more about my projects and check out my list of publications. I have served on the organizing and program committees of top database and systems conferences. Every summer, I enjoy working with students during their internships at Microsoft Research.

Recent News

  • A paper I led at MSR, with my intern and others, on learning data layouts in storage for big data analytics will appear at SIGMOD 2020. We propose a data structure called a qd-tree (built using deep RL) to layout data blocks in a workload-guided manner. Easy to integrate into DB as well!
    • Zongheng Yang, Badrish Chandramouli, et al. Qd-tree: Learning Data Layouts for Big Data Analytics. SIGMOD 2020. [pdf][arXiv:2004.10898]
  • We have designed and built an updatable and adaptive learned index called ALEX. The paper will appear at SIGMOD 2020, and you can find a copy below.
    • Jialin Ding et al. ALEX: An Updatable Adaptive Learned Index. SIGMOD 2020. [pdf]
  • I introduced the SimpleStore umbrella research project at HPTS. See my slides here.
  • A research paper and demo on FishStore, for fast ingestion, storage, and indexing of raw data, appeared at SIGMOD 2019 and VLDB 2019.
    • Badrish Chandramouli, Dong Xie, Yinan Li, Donald Kossmann. FishStore: Fast Ingestion and Indexing of Raw Data. VLDB 2019, Los Angeles, California, USA, August 2019 (demo). [pdf]
    • Dong Xie, Badrish Chandramouli, Yinan Li, Donald Kossmann. FishStore: Faster Ingestion with Subset Hashing. SIGMOD 2019, Amsterdam, Netherlands, June 2019. [pdf]
  • We have a fresh take on the age-old database recovery problem. Learn about Concurrent Prefix Recovery (CPR) in our research paper at SIGMOD 2019.
    • Guna Prasaad, Badrish Chandramouli, Donald Kossmann. Concurrent Prefix Recovery: Performing CPR on a Database. SIGMOD 2019, Amsterdam, Netherlands, June 2019. [pdf]
  • A short paper on our open-source system, CRA (Common Runtime for Applications), appeared at ICDE 2019. CRA is the backbone distributed runtime behind Quill and Ambrosia.
    • Ibrahim Sabek, Badrish Chandramouli, Umar Farooq Minhas. CRA: Enabling Data-Intensive Applications in Containerized Environments. ICDE 2019, Macau, China, April 2019. [pdf][tech-report]

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