Apache Hadoop and the big data ecosystem have exploded in popularity and most developers are at least loosely familiar with it. Needless to say, there are many pieces of the Hadoop ecosystem that work together to form a big data platform. It's mostly an a-la-carte world in which you combine the pieces you want, each having different uses, or makes different trade-offs between ease-of-coding and performance. What does Solr have to do with Hadoop, you may ask? Read on.
As an alternative to a standard filesystem, Solr can store its indexes in Hadoop Distributed File System (HDFS). HDFS acts like a shared filesystem for Solr, somewhat like how networked storage is (for example, a SAN), but is implemented at the application layer instead of at the OS or hardware layer. HDFS offers almost limitless growth, and you can increase storage incrementally without restarting or reconfiguring the server processes supporting it. HDFS has redundancy too, although this is extra-redundant...