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Comparing a column-oriented RDBMS with parallel query execution versus hadoop is a joke in the first place. Hadoop is extremely slow. That's nothing new. This is not an apples-to-apples comparison whatsoever.

How does it compare against Greenplum or Aster or Vertica and is it more cost-effective? Those are important questions.

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Comparing Redshift against Hadoop+Hive is reasonable. As you pointed out... the technologies are very different. However, there is a large overlap in use cases.

I strongly disagree. I am (or was) using both Hadoop and HBase and they are useful for very different purposes (huge amounts of nonstructured data, possibly with difficult-to-predict use cases versus structured data). Also note that Hive is just a layer over Hadoop with DB-like syntax, it doesn't make Hadoop a DB. It is still running MR queries beneath it.

Especially given that Redshift, Greenplum and Aster directly build on or incorporate technology from PostgreSQL.

This is true for Vertica as well.

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