Archive for Month: January 2013

Sharding: In Theory and Practice (Part Three)

Part Three: What’s in a Shard? In the first two posts of this series, I offered a perspective on the origins of database sharding and described the architectural problems with algorithmic sharding that led LiveJournal and TypePad to use dynamic sharding to scale. The next challenge of a sharded architecture […]

Scale Up vs. Scale Out

When I talk to database developers and database architects, they’re often consumed with how to deal with the challenges of scaling their databases in the face of rapid growth while simultaneously focusing on applications changes to help their businesses grow. They talk about hiring expensive performance consultants, ongoing tuning and […]

Why I Joined Clustrix

  I recently joined Clustrix as vice president of engineering after more than 25 years in databases and information management. Throughout my career I have focused on innovations in parallel database technology and analytics—primarily in building business-critical products for the enterprise—and ClustrixDB is no exception. Here’s why… I Believe in […]

Sharding: In Theory and Practice (Part Two)

  Part Two: The Differences Between Algorithmic and Dynamic Sharding In my last post, I pointed to the LiveJournal model as an example of sharding on which many recent Internet companies have based their own implementations. To understand the design decisions of a sharded environment, let’s discuss the differences between […]

Announcing the Limited Preview of Clustrix 5.0 on Amazon Web Services

SQL Database Clustrix Announces Preview of Latest Version 5.0 in the AWS Marketplace The move to cloud computing is changing the face of the computer industry, and at the heart of this change is Big Data and the scale-out platforms that enable it. As demand grows, applications add new computing […]