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Скачать или смотреть Introduction to Apache Cassandra by Patrick McFadin

  • Data Council
  • 2013-11-19
  • 729
Introduction to Apache Cassandra by Patrick McFadin
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Описание к видео Introduction to Apache Cassandra by Patrick McFadin

In this introduction to Cassandra, Patrick McFadin, Chief Evangelist for Apache Cassandra at DataStax, gives a presentation and an introduction to why Apache Cassandra is a key player in database technologies. Both large and small companies alike choose to use Apache Cassandra as their database solution and Patrick will be presenting on why they made this choice. Patrick will also be discussing the architecture of Apache Cassandra, including: data modeling, time-series storage and replication strategies, providing a holistic overview of how Apache Cassandra works and the best way to get started. This talk was recorded at the Big Data Gurus meetup at Samsung R&D.

Bio: Prior to working for DataStax, Patrick was the Chief Architect at Hobsons, an education services company. His responsibilities included ensuring product availability and scaling for all higher education products. Prior to this position, he was the Director of Engineering at Hobsons which he came to after they acquired his company, Link-11 Systems, a software services company. While at Link-11 Systems, he built the first widely popular CRM system for universities, Connect. He obtained a BS in Computer Engineering from Cal Poly, San Luis Obispo and holds the distinction of being the only recipient of a medal (as anyone can find out) for hacking while serving in the US Navy.

Here are some links for Apache Cassandra:
http://cassandra.apache.org/
http://en.wikipedia.org/wiki/Apache_C...

Here is some background on Apache Cassandra:
Apache Cassandra is a free, open-source, distributed storage system for managing large amounts of structured data. It differs from traditional relational database management systems in some significant ways. Cassandra is designed to scale to a very large size across many commodity servers, with no single point of failure, and provides a simple schema-optional data model designed to allow maximum power and performance at scale.

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