InfoQ Homepage Performance & Scalability Content on InfoQ
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Understanding Java Garbage Collection and What You Can Do about It
Gil Tene explains the workings of a garbage collector: terminology, metrics, fundamentals, key mechanisms, classification of current GCs, the “Application Memory Wall” problem, and details Azul C4 GC.
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Case Study: Riak on Drugs (and the Other Way Around)
Kresten Krab Thorup discusses a MySQL project that was moved to Riak for high availability, scalability and to run off multiple data centers, sharing the experiences, pitfalls and lessons learned.
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SQLFire: Scalable SQL instead of NoSQL
Jags Ramnaraya presents SQLFire and how SQL can be used for modern data stores backing online highly scalable applications by using a different consistency model and sharing nothing persistence.
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Building Scalable Systems: an Asynchronous Approach
Theo Schlossnagle expresses his opinion on Big Data, NoSQL, cloud, system architecture and design, then he discusses the benefit of using asynchronous queues for building scalable systems.
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Do You Really Get Memory?
Jevgeni Kabanov creates a CPU model in Java in an attempt to explain the underlying mechanism of memory performance bottlenecks and the need for a correlated hardware, OS and JVM improvement.
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Above the Clouds: Introducing Akka
Jonas Bonér introduces Akka, a JVM platform that wants to address the complex problems of concurrency, scalability and fault tolerance using Actors, STM and self-healing from crashes.
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Why I Chose MongoDB for guardian.co.uk
Mat Wall makes a journey through Guardian’s online history, outlining technologies used – Perl/CGI, CMS, J2EE, Oracle-, and explaining why they chose a NoSQL solution – MongoDB - and its advantages.
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Building Solid Distributed Applications with Haskell and Riak
Bryan O'Sullivan discusses the design considerations and types usage when building distributed systems with Haskell and Riak, starting from a case study of a system using vector clocks.
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Big Data in Real Time at Twitter
Nick Kallen discusses how Twitter handles large amounts of data in real time by creating 4 data types and query patterns -tweets, timelines, social graphs, search indices-, and the DBs storing them.
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Beyond The Data Grid: Coherence, Normalization, Joins and Linear Scalability
Ben Stopford presents ODC, a highly distributed in-memory normalized NoSQL datastore designed for scalability, based on normalized data, Snowflake Schema, and Connected Replication pattern.
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Netflix’s Cloud Data Architecture
Siddharth Anand overviews Netflix’s business model, then he explains why they chose Amazon AWS, and how they moved their data into the cloud using a NoSQL solution.
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More Best Practices for Large-Scale Websites: Lessons from eBay
Randy Shoup: Partition Everything, Asynchrony Everywhere, Automate, Everything Fails, Embrace Inconsistency, Expect (R)evolution, Dependencies Matter, Respect Authority, Data, Custom Infrastructure.
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