InfoQ Homepage Performance & Scalability Content on InfoQ
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Facebook Messages: Backup & Replication Systems on HBase
Nicolas Spiegelberg discusses Facebook Messages built on top of HBase, the systems involved and the scaling challenges for handling 500TB of new data per month.
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Racing Thru the Last Mile: Cloud Delivery Web-Scale Deployment
Alex Papadimoulis discusses various deployment strategies, scalable delivery, with examples from real-world organizations such as AllRecipes.com, Twitter, and Google.
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Architectural Patterns for High Availability
Adrian Cockcroft presents Netflix globally distributed architecture, the benchmarks used, scalability issues, and the open source components their implementation is based upon.
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Timelines at Scale
Raffi Krikorian explains the architecture used by Twitter to deal with thousands of events per sec - tweets, social graph mutations, and direct messages-.
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(un)Common Sense
Mike Solomon shares some of the experiences and lessons learned scaling YouTube over the years.
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Scaling Pinterest
Yashwanth Nelapati and Marty Weiner share lessons learned growing Pinterest: sharding MySQL, caching, server management, all on Amazon EC2.
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Running the Largest Hadoop DFS Cluster
Hairong Kuang explains how Facebook uses HDFS to store and analyze over 100PB of user log data.
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Scaling Scalability: Evolving Twitter Analytics
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.
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Petabyte Scale Data at Facebook
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.
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Facebook News Feed: Social Data at Scale
Serkan Piantino discusses news feeds at Facebook: the basics, infrastructure used, how feed data is stored, and Centrifuge – a storage solution.
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Not Your Father’s Transaction Processing
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.