Asserting the winners of the 2021 Subsequent-generation Knowledge Infrastructure request for proposals

In April 2021, Facebook launched the Request for Proposals (RFP) for the next generation of data infrastructure. Today we announce the winners of this award.
The Facebook Core Data and Data Infra teams were interested in proposals that sought innovative solutions to the challenges that still exist in the data management community. The areas of interest included the following topics:

• Processing of extensive inquiries
• Physical layout and IO optimizations
• Data management and processing on a global level
• Convergent architectures for data wrangling, machine learning and analytics
• Advances in testing and verification of storage and processing systems

Read our Q&A with database researchers Stavros Harizopoulos and Shrikanth Shankar to learn more about database research on Facebook, the purpose of this call, and the inspiration behind the call.

The team has reviewed 109 high quality proposals and we are pleased to announce the 10 winning proposals and six finalists. Thank you to everyone who took the time to submit a proposal and congratulations to the winners.

Research Award Winner

Holistic optimization for parallel query processing
Paraschos Koutris (University of Wisconsin – Madison)

SCALER – Scalable vector processing of SPJG queries
Wolfgang Lehner, Dirk Habich (Technical University of Dresden)

AnyScale transactions in the cloud
Natacha Crooks, Joe Hellerstein (University of California, Berkeley)

Proudi: predictability on unpredictable data infrastructure
Haryadi S. Gunawi (University of Chicago)

Make irregular division practical
Spyros Blanas (Ohio State University)

Pushdown to dynamic join processing in Presto
Daniel Abadi, Chujun Song (University of Maryland, College Park)

A learned persistent key value store
Tim Kraska (Massachusetts Institute of Technology)

Building global systems with a flexible consensus substrate
Faisal Nawab (University of California, Irvine)

Run-time optimized analyzes with compilation notes
Anastasia Ailamaki (Swiss Federal Institute of Technology, Lausanne)

Flexible planning for machine learning computing close to storage
Ana Klimovic, Damien Aymon (ETH Zurich)

Finalists

Next generation data origin / data governance
Tim Kraska, Michael Cafarella, Michael Stonebraker (Massachusetts Institute of Technology)

Optimization of commitment latency for geographically dispersed transactions
Xiangyao Yu (University of Wisconsin-Madison)

Semantic optimization of recursive queries
Dan Suciu (University of Washington)

On the way to a disaggregated database for future data centers
Jianguo Wang (Purdue University)

Uniform data systems for structured and unstructured data
Matthew Zaharia, Christos Kozyrakis (Stanford University)

Combine machine learning and analytics under a single data engine
Stratos Idreos (Harvard University)