One of the best aspects of NoSQL databases is a scale-out architecture that easily supports database growth using inexpensive, commodity hardware. This feature is one of many that contributed to MongoDB’s growing popularity as a standard for modern application building.
Scaling over commodity hardware results in significantly lower cost than operating older, relational database technology. For example, deployments of MongoDB, the most popular NoSQL database, typically use cheap, Linux servers that cost as little as $3,000. In contrast, a relational deployment can cost in the six-figure range.
There is a tradeoff with using NoSQL technology though as you will find additional complexities in capacity planning and database provisioning since you are running across multiple servers instead of just one server as you would with a relational database.
When MongoDB customers set out to deploy the database, they ask some common questions, such as: How many replicas are needed? When should I shard? How much RAM will I need for my working set? SSD or HDD?
To answer these questions, you should carefully review the factors that will determine capacity requirements such as the volume of queries, data access patterns, indexing, and working set size. MongoDB offers the benefit of on demand, automatic provisioning with our management solutions: Ops Manager for on-prem deployments or Cloud Manager if you choose to run in the cloud. Ops Manager can deploy on MongoDB on any connected server. Cloud Manager has the added benefit of integration with Amazon Web Services which makes it easy to get started with an optimal configuration for MongoDB.
Find out more about these management solutions on our website. If you plan on running a cloud-based deployment of MongoDB, trying out Cloud Manager is risk-free for 30 days. To get started on your free trial, sign up for Cloud Manager today.