Of course the approach quickly hits a limitation if the dataset is too big to be replicated on every app server, or if low-latency updates are required.
This is handled by grouping nodes together physically, and calling the resulting bundle a datacenter.
Data is stored using a Cassandra-like algorithm, that locates the data on each node in the cluster.
This solves both the "too much data for one machine" and the low-latency problem. Now the data just needs to fit in a single datacenter.
This is handled by grouping nodes together physically, and calling the resulting bundle a datacenter.
Data is stored using a Cassandra-like algorithm, that locates the data on each node in the cluster.
This solves both the "too much data for one machine" and the low-latency problem. Now the data just needs to fit in a single datacenter.