InfoQ Homepage BigTable Content on InfoQ
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Scaling Pinterest
Details on Pinterest's architeture, its systems -Pinball, Frontdoor-, and stack - MongoDB, Cassandra, Memcache, Redis, Flume, Kafka, EMR, Qubole, Redshift, Python, Java, Go, Nutcracker, Puppet, etc.
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Graph Computing at Scale
Matthias Broecheler discusses graph computing, introducing the Aurelius graph cluster enabling graph computing at scale by building on distributed systems like Cassandra, HBase, and Hadoop.
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Cloud Computing at Google
Randy Shoup details some of the pieces forming Google’s technology stack, BigTable, Megastore, Dremel, virtualization, etc. and the design principles of their their cloud-based applications.
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Apache Cassandra Anti Patterns
Matthew Dennis covers the most common mistakes made with Cassandra that he has noticed being made both in deployment and code.
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Hadoop and Cassandra, Sitting in a Tree ...
Jake Luciani introduces Brisk, a Hadoop and Hive distribution using Cassandra for core services and storage, presenting the benefits of running Hadoop in a peer-to-peer masterless architecture.
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Keeping Movies Running Amid Thunderstorms!
Siddharth Anand presents how Netflix’s architecture evolved from a traditional 3-tier configuration to a cloud-based one, detailing the scalability and fault tolerant issues encountered.
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Polyglot Persistence for Java Developers - Moving Out of the Relational Comfort Zone
Chris Richardson shows how he ported a relational database to three NoSQL data stores: Redis, Cassandra and MongoDB.
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SimpleGeo: Staying Agile at Scale
Mike Malone discusses principles of good and bad (software) architecture determining SimpleGeo’s architecture: deal with change, embrace failure, phased adoption, balanced security, and others.
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NoSQL @ Netflix
Siddharth “Sid” Anand explains the technical details behind the move from Oracle used inside their data center to SimpleDB and S3 in the cloud, and from there to Cassandra.
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NoSQL at Twitter
Ryan King presents how Twitter uses NoSQL technologies - Gizzard, Cassandra, Hadoop, Redis - to deal with increasing data amounts forcing them to scale out beyond what the traditional SQL has to offer
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Abstractions at Scale–Our Experiences at Twitter
Marius Eriksen considers that leaky abstractions lead to scalability issues, while those providing narrow access to explicit resources - map-reduce, shared-nothing web apps, big table - scale better.
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Adopting Apache Cassandra
Eben Hewitt introduces the Apache Cassandra project to those interested in getting a quick clear picture of what Cassandra is, what are its main features, what is the the data model used and the API.