Storage architecture can have a direct impact on MongoDB performance. Traditional relational databases were designed around legacy SAN devices and required that the storage systems were dedicated to the database. If you wanted more performance you purchased a larger array. With NoSQL databases, the model has been flipped upside down. These databases are designed from the ground up to be distributed. More hosts equals more performance. By leveraging solid-state drive technology with concepts like storage virtualization, quality of service and horizontal scaling, next generation storage systems like SolidFire are able to combine the comforts of traditional dedicated storage performance with the simplicity and scalability expected in a MongoDB environment.
The architecture of MongoDB makes it ideal for large scale deployments. By tuning MongoDB to work with a next generation storage system, database administrators can achieve consistent, repeatable IO performance with ultra low latency in a highly scalable, extremely flexible database environment.
Join Chris Merz as he walks through a real-world example to show how to:
- Architect MongoDB with SolidFire storage for a large scale production cloud environment
- Traverse the technology stack to identify performance bottlenecks
- Optimize IO performance and latency
- Normalize performance under load
- Maintain performance at scale