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Scaling a Relational Database for the Cloud age | Citus Data

Download the slides: https://dataeng.co/2Lu45JS

ABOUT THE TALK:

Years ago when working at Amazon on shopping cart infrastructure and the precursor to DynamoDB, my co-founder and I realized that while distributed key value stores were useful for a few use-cases, we missed many of the benefits of relational databases: transactions, joins, and the power of the lingua franca of RDBMS’s: SQL. So we challenged ourselves to modernize the traditional relational database, to take a robust open source relational database and transform it into a distributed database.

This talk is about my team’s journey to create a more modern relational database. I’ll talk about the distributed systems problems we had to solve in order to scale out the Postgres open source database, in order to achieve parallelism and a concomitant increase in performance. I'll describe the architecture of the distributed query planner; how we extend traditional relational algebra operators to plan distributed queries and scale reads. I’ll also describe distributed deadlock detection, and how that enabled us to scale out transactions spanning multiple machines.

ABOUT THE SPEAKER:

Sumedh is the co-founder & VP Engineering at Citus Data. Previously he worked at Amazon as a Software Engineer. He holds a Master's degree in Computer Science from Stanford University.

ABOUT DATA COUNCIL:
Data Council (https://www.datacouncil.ai/) is a community and conference series that provides data professionals with the learning and networking opportunities they need to grow their careers. Make sure to subscribe to our channel for more videos, including DC_THURS, our series of live online interviews with leading data professionals from top open source projects and startups.

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Видео Scaling a Relational Database for the Cloud age | Citus Data канала Data Council
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26 мая 2018 г. 4:16:36
00:33:25
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