Granular Archival and Nearline Storage Using MySQL, S3 and SQS

Cloud Computing
Location: Ballroom A

A well designed archival strategy can allow your application to manage larger amounts of data at a lower total cost with better performance on your MySQL queries. In this session we will discuss how to design your data for efficient archival and walk through an execution plan using Amazon SQS and S3 with MySQL and code examples in Ruby.

Here are some topics we’ll cover:

  • What an archival integrated data model looks like
  • What kinds of data are good candidates for archival
  • Determining the best chunk size for archival
  • Designing your schema to support archival
  • Using the Actor pattern for archive/restore operations

Walt Jones


I have 15 years experience in data architecture and protocol design for networks, storage, and streaming media.

I currently work at SEOmoz where I am applying my experience with data in motion to distributed cloud data architectures.

  • EnterpriseDB
  • Amazon Web Services
  • Clustrix
  • Continuent
  • Facebook
  • HTI Consultoria e Tecnologia
  • Monty Program
  • Percona
  • Rackspace Hosting
  • Schooner Information Technology
  • SkySQL
  • Xeround

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