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Running the Largest Hadoop DFS Cluster

Posted by Hairong Kuang  on  Mar 15, 2013 5

Hairong Kuang explains how Facebook uses HDFS to store and analyze over 100PB of user log data.

Scaling Scalability: Evolving Twitter Analytics

Posted by Dmitriy Ryaboy  on  Jan 13, 2013

Dmitriy Ryaboy shares some of the lessons learned scaling Twitter’s analytics infrastructure: Data loves a schema, Make data sources discoverable, and Make costs visible.

Scaling Tumblr

Posted by Ken Little  on  Dec 18, 2012

Ken Little discusses the architecture and infrastructure employed by Tumblr.

Petabyte Scale Data at Facebook

Posted by Dhruba Borthakur  on  Dec 17, 2012 3

Dhruba Borthakur discusses the different types of data used by Facebook and how they are stored, including graph data, semi-OLTP data, immutable data for pictures, and Hadoop/Hive for analytics.

Facebook News Feed: Social Data at Scale

Posted by Serkan Piantino  on  Nov 26, 2012 1

Serkan Piantino discusses news feeds at Facebook: the basics, infrastructure used, how feed data is stored, and Centrifuge – a storage solution.

Not Your Father’s Transaction Processing

Posted by Michael Stonebraker  on  Oct 26, 2012 1

Michael Stonebraker compares how RDBMS, NoSQL and NewSQL support today’s big data transaction processing needs. He also introduces VoltDB, an in-memory NewSQL database.

Real-Time Delivery Architecture at Twitter

Posted by Raffi Krikorian  on  Oct 23, 2012 3

Raffi Krikorian details Twitter’s timeline architecture, its “write path” and “read path”, making it possible to deliver 300k tweets/sec.

The Startup Hangover: Supporting 15M Users

Posted by Phil Calçado  on  Oct 18, 2012

Phil Calçado presents SoundCloud’s approach to dealing with scalability issues when their user number grew beyond what they initially could support by creating services in various languages.

MongoDB - Born in the Cloud

Posted by Ross Lawley  on  Oct 15, 2012

Ross Lawley introduces MongoDB, explaining why it is a good solution for cloud deployment.

Event Processing at Massive Scale

Posted by Uri Cohen  on  Sep 13, 2012 6

Uri Cohen discusses several types of queues with their pros and cons used in financial and trading industries for highly parallelized data processing.

Netflix: Movies, When You Want, Where You Want, from the Cloud!

Posted by Jeremy Edberg  on  Sep 07, 2012

Jeremy Edberg discusses running Netflix services on AWS: storage, streaming and scaling solutions, multi-region deployments, why cloud over private data center, and architectural snapshots.

Working with MIG

Posted by David Dawson and Marcus Kern  on  Aug 22, 2012

David Dawson and Marcus Kern share lessons learned creating a high-performance mass audience participation system using NoSQL.

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