At a high level, Kudu is a new storage manager that enables durable single-record inserts, updates, and deletes, as well as fast and efficient columnar scans due to its in-memory row format and on-disk columnar format. This architecture makes Kudu very attractive for data that arrives as a single record at a time or that may need to be modified at a later time.
Today, many users try to solve this challenge via a Lambda architecture, which presents inherent challenges by requiring different code bases and storage for the necessary batch and real-time components. Using Kudu and Impala together completely avoids this problematic complexity by easily and immediately making data inserted into Kudu available for querying and analytics via Impala. (For more technical details on how Impala and Kudu work together for analytical workloads, see this post.)
I’d jokingly say “Someday, somebody’s going to reinvent the relational database inside of Hadoop.” But it seems like that’s less of a joke than a medium-term prediction.