Portrait of Badrish Chandramouli

Badrish Chandramouli

Senior Researcher


Badrish Chandramouli is a senior researcher in the database group at Microsoft Research.  He is broadly interested in creating technologies to perform near-real-time and offline big data analytics for Cloud applications. Since 2008, Badrish has been working on the streams project – this work shipped commercially in 2010 as the Microsoft StreamInsight engine. His current project, Trill, is a new analytics engine that is being 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).



Established: September 19, 2013

Trill is a high-performance in-memory incremental analytics engine. It can handle both real-time and offline data, and is based on a temporal data and query model. Trill can be used as a streaming engine, a lightweight in-memory relational engine, and as a progressive query processor (for early query results on partial data). You can learn more about Trill from the publications below, or from our slides here pdf | pptx.


Established: September 12, 2013

Tempe is a web service for exploratory data analysis. Below are images of the notebook pages mentioned in our submission to ICSE 2014.

User Experience with Big Data

Established: May 24, 2012

Big data analytics requires new workflows: high latency queries, massively-parallel code, and cloud computing infrastructures all make handling a big dataset different (and harder) than working on a local machine. We are exploring user experiences for analysts, and thinking about new ways to deal with big datasets. BigDataUX: building a better user experience for Big Data. Lots of different definitions can be found for "big data," but they all have one aspect…


Established: November 21, 2011

In the streams research project, we propose novel architectures, efficient processing techniques, models, and applications to support time-oriented queries over real-time and offline data streams. Our current focus in the project centers around Trill, a high-performance streaming analytics engine that is now used across Microsoft. Our currect focus areas include efficient query processing, scale-out, resiliency, streaming state management, and unstructured data support.











Microsoft CEP Server and Online Behavioral Targeting
Mohamed Ali, Ciprian Gerea, Balan S. Raman, Beysim Sezgin, Tiho Tarnavski, Tomer Verona, Ping Wang, Peter Zabback, Asvin Ananthanarayan, Anton Kirilov, Ming Lu, Alex Raizman, Ramkumar Krishnan, Roman Schindlauer, Torsten Grabs, Sharon Bjeletich, Badrish Chandramouli, Jonathan Goldstein, Sudin Bhat, Ying Li, Vincenzo Di Nicola, Xianfang Wang, David Maier, Stephan Grell, Olivier Nano, Ivo Santos, in International Conference on Very Large Data Bases (VLDB), Lyon, France, August 1, 2009, View abstract, Download PDF




My main ongoing research projects include:

  • Trill: Since early 2012 when he started the Trill project with colleagues, Badrish has been working on building Trill as a .NET based high-performance incremental analytics engine. Trill is a library with a new architecture that provides best-of-breed or better performance across a diverse range of analytics styles and latency needs. As described in this blog post from MSR, Trill is widely used within Microsoft, for example, in the Bing advertising platform and as part of the public-facing Azure Stream Analytics service.
  • Tempe: Tempe is a visual Web-based analytics environment for ad-hoc real-time and offline analytics. Part of the big data user experience project, Tempe provides a rich environment for authoring Trill logic and visualizing it, and at the same time makes it easy to deploy the logic into any Cloud application.

In the context of these projects, Badrish has worked on diverse research areas such as progressive analytics, sorting, pattern detection, query processing, and distributed systems.