In partitioned databases, trading some consistency for availability can lead to dramatic improvements in scalability.

Web applications have grown in popularity over the past decade. Whether you are building an application for end users or application developers (i.e., services), your hope is most likely that your application will find broad adoption—and with broad adoption will come transactional growth. If your application relies upon persistence, then data storage will probably become your bottleneck.

There are two strategies for scaling any application.
The first, and by far the easiest, is vertical scaling: moving
the application to larger computers. Vertical scaling works

reasonably well for data but has several limitations. The most obvious limitation is outgrowing the capacity of the largest system available. Vertical scaling is also expensive, as adding transactional capacity usually requires purchasing the next larger system. Vertical scaling often creates vendor lock, further adding to costs.

Horizontal scaling offers more flexibility but is also considerably more complex. Horizontal data scaling can be performed along two vectors. Functional scaling involves grouping data by function and spreading func-

DAN PRITCHETT, EBAY