MongoDB: The Definitive Guide, 2nd Edition

Foreword

Jeremy Zawodny

Craigslist Software Engineer

In the last 10 years, the Internet has challenged relational databases in ways nobody could have foreseen. Having used MySQL at large and growing Internet companies during this time, I’ve seen this happen firsthand. First you have a single server with a small data set. Then you find yourself setting up replication so you can scale out reads and deal with potential failures. And, before too long, you’ve added a caching layer, tuned all the queries, and thrown even more hardware at the problem.

Eventually you arrive at the point when you need to shard the data across multiple clusters and rebuild a ton of application logic to deal with it. And soon after that you realize that you’re locked into the schema you modeled so many months before.

Why? Because there’s so much data in your clusters now that altering the schema will take a long time and involve a lot of precious DBA time. It’s easier just to work around it in code. This can keep a small team of developers busy for many months. In the end, you’ll always find yourself wondering if there’s a better way—or why more of these features are not built into the core database server.

Keeping with tradition, the Open Source community has created a plethora of “better ways” in response to the ballooning data needs of modern web applications. They span the spectrum from simple in-memory key/value stores to complicated SQL-speaking MySQL/InnoDB derivatives. But the sheer number of choices has ...