A good knowledge of data structures always helps in designing good systems, whether we are working with relational databases or NOSQL databases. However, this knowledge is much more important when working with NOSQL systems. One important fact to remember is that while a lot of optimization for SQL based solutions is during query time, NOSQL solutions (especially Hadoop/HBase) are design time optimized. You design an optimized schema and the queries are almost straight forward.
Hbase is counterintuitive for any one with experience of row-based traditional Relational Database System. The major difference between Hbase or any of the other Google Bigtable clones with RDBMS, is that unlike RDBMS which mainly focuses on the question how the data is going to be stored, they instead focuses on how to access the data. That is RDBMS model mainly deals with identifying the entities and their relationship thus mandating the normalization of data for ACID assurance.
Big Talk About BigTable
Relational Databases have hegemony on the way data has been stored. Proponents of Relational Database emphasize on normalization for valid reasons. Maintainability, Integrity (summed up in ACID) and Security has been the primary focus of classical relational database problems. Backed by Moore’s law it was easy to theorize that processing speed would inevitably be a trivial factor over other engineering problems like consistency and integrity. In some sense that is true but hitherto unaccounted for were sites like Google and Facebook which needed to process PetaBytes of data every second in real time.