InfoQ Homepage Columnar Databases Content on InfoQ
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A Distributed Transactional Database on Hadoop
John Leach explains using HBase co-processors to support a full ANSI SQL RDBMS without modifying the core HBase source, showing how Hadoop/HBase can replace traditional RDBMS solutions.
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Cassandra, Couchbase and Spring Data in the Enterprise
The authors focus on POJO persistence over Cassandra, including automatic Cassandra schema generation and Spring context configuration using both XML and Java.
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Zen: Pinterest's Graph Storage Service
This talk goes over the design motivation for Zen and describe its internals including the API, type system and HBase backend.
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Unleash the Power of HBase Shell
Jayesh Thakrar shows what can be done with irb, how to exploit JRuby-Java integration, and demonstrates how the Shell can be used in Hadoop streaming to perform complex and large volume batch jobs.
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Going Native with Apache Cassandra
In this solutions track talk, sponsored by DataStax, Johnny Miller introduces the Cassandra native protocol, native drivers and CQL, explaining how to query Cassandra without Trift or RPC.
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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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Spanner - Google's Distributed Database
Sebastian Kanthak details how Spanner relies on GPS and atomic clocks to provide two of its innovative features: Lock-free strong reads and global snapshots consistent with external events.
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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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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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Spring Data - NoSQL - No Problems...
Peter Bell introduces 4 NoSQL categories –Key-Value, Document, Column, Graph - and explains how one can use Spring Data to work with such data stores.