This whole post is based on the assumption that "Splout SQL" is something "novel" and "necessary". To me these are not clear, though.

I have prototyped some Big Data systems in the past months where we use Sqoop for exporting Hadoop to proprietary SQL databases. So far, so good. I wonder what are the real advantages of using Splout SQL in such cases.

Three things differentiate Splout SQL from using Sqoop for exporting to an existing SQL database: 1) Scalability: Relational databases rarely scales, or are too expensive for big volumes of data. They don't work well with Hadoop. 2) Update isolation: In Splout SQL, database updating never affects serving queries as it is performed in a Hadoop cluster. 3) Atomicity: Datasets are deployed atomically in Splout SQL. That avoids inconsistency problems that arises in RDMS when updating existing databases.