In the world of Big Data, scaling out is the norm. However, many Big Data deployments are trapped in a sea of small box clusters.
With the advent of scalable platforms like Scylla, node performance is no longer an issue and doubling the size of the nodes can double the available storage, memory, and processing power. So what stops people from going big in the Cloud Native world?
Join us to learn the pros and cons of large nodes, and explore why people resist using big machines, including:
- Is the cost of recovering from failures higher in larger nodes?
- Does performance increase linearly as machines get bigger?
- Does cluster performance suffer for the entire time of recovery from failures?