The SolrCloud architecture

Scaling proceeds in two ways when it comes to handling large amounts of data, horizontally or vertically. Vertical scaling deals with the problems of handling large data by adding bigger and bigger machines. Suppose a single machine which has 4 GB of RAM and 4 CPU can handle a concurrency of 100 queries per second on a data size of say 8 GB. As the amount of data increases, the amount of processing required for serving the queries also increases. Therefore, if the data size goes to 16 GB, the query concurrency that the same machine can handle will be 75 queries instead of 100. For vertical scaling, we would replace the current 4 GB + 4 CPU machine with an 8 GB + 8 CPU machine, which should again be able to serve a concurrency of 100 queries per second on a data size of 16 GB. Horizontal scaling would mean that we add another machine of the same configuration 4 GB RAM + 4 CPU to the system and divide 16 GB of data into two parts of 8 GB each. Each machine now hosts...