InfoQ Homepage Infrastructure Content on InfoQ
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Stuart Halloway on Datomic, Clojure, Reducers
Stuart Halloway explains Datomic, programming transactional behavior with Datomic, Datalog and logic programming, programming with values, Clojure Reducers and much more.
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Max Sklar on Machine Learning at Foursquare
Max Sklar talks about machine learning at Foursquare, the use of Bayesian Statistics and other methods to build Foursquare's recommendation system and much more.
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Rich Hickey and Justin Sheehy about Datastores, NoSql and CAP
Rich Hickey and Justin Sheehy talk about scalability and transactionability of datastores. They explain tradeoffs for achieving read and/or write scalability on top of Datomic and Riak.
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Mike Stolz on NoSQL and Big Data Design Patterns
In this interview recorded at QCon New York 2012 Conference, VMWare's Mike Stolz talks about the design patterns that help with processing and analyzing the unstructured data. He also explains the patterns for combining Fast Data with Big Data in finance applications as well as the role of in-memory databases in NoSQL database space.
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Rupert Smith on Low-Latency Java Programming, FPGAs
Rupert Smith explains how to write low-latency code on plain JVMs (not realtime VMs) and how to avoid GC pauses. Also: how to exploit the capabilities of FPGAs to improve performance.
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James Spooner on Data Flow Parallelism and Hardware Acceleration
James Spooner explains how Data Flow Parallelism works and how it helps to design efficient parallel algorithms. Also: OOP vs. Parallelism.
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Andrew Watson On The State of OMG, UML, CORBA, DDS
Andrew Watson talks about the work of the OMG, where CORBA is alive and well (hint: in your car), UML and UML Profiles vs. custom Modeling languages, DDS and other middleware, and much more.
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Big Data Architecture at LinkedIn
In this interview at QCon London, LinkedIn’s Sid Anand discusses the problems they face when serving high-traffic, high-volume data. Sid explains how they’re moving some use cases from Oracle to gain headroom, and lifts the hood on their open source search and data replication projects, including Kafka, Voldemort, Espresso and Databus.
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Optimizing for Big Data at Facebook
Hive co-creator Ashish Thusoo describes the Big Data challenges Facebook faced and presents solutions in 2 areas: Reduction in the data footprint and CPU utilization. Generating 300 to 400 terabytes per day, they store RC files as blocks, but store as columns within a block to get better compression. He also talks about the current Big Data ecosystem and trends for companies going forward.
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Patrick Debois on the State of DevOps
Patrick Debois discusses the ideas behind DevOps, popular DevOps tools like Chef and Puppet, DevOps vs NoOps, and much more.
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Rich Hickey on Datomic: Datalog, Databases, Persistent Data Structures
Rich Hickey explains the ideas behind the Datomic database: why Datalog is used as the query language, the functional programming concepts at its core, the role of time in the DB and much more.
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Operating Node.js in Production, with Bryan Cantrill
Bryan talks about the challenges of operating Node.js in real production environments and the experiences he had working with it at Joyent. He also talks about DTrace, SmartOS, V8 and compares with other platforms.
