With NoSQL (and Hadoop in particular) being one of the darlings of the new "Big Data" era of the last few years, I think that one of the first questions I have when choosing a NoSQL option is - "Should I be choosing a NoSQL option" or is a relational database the correct option for me. I know that at one of the DC "BigData" meetups, or TechDC meetups, Living Social talked about their strategy of saving all data into their NoSQL solution and determining it's usage later. Does your book cover the question of when it is appropriate to use Hadoop, and when your solution may in fact be better implemented in a RDBMS? Also, do you feel that most things that are implemented in RDMBS systems could just as efficiently (or more efficiently) be translated to a Hadoop solution?
And once you have made the decision to go down the NoSQL route, many of us still have to determine the technology.
"Facebook created Cassandra, Google created BigTable and MapReduce, Amazon created SimpleTable and LinkedIn created Project Voldemort" etc, etc. We know there are quite a few solutions out there, and I'm sure that the strength of the ecosystem plays a large part in what the correct choice is. Do you cover the topic of choosing a NoSQL solutions, and argue the case for why Hadoop is the correct choice, or is the book targeted at people who have already made that decision.
Thanks for your time and knowledge!
David
And once you have made the decision to go down the NoSQL route, many of us still have to determine the technology.
"Facebook created Cassandra, Google created BigTable and MapReduce, Amazon created SimpleTable and LinkedIn created Project Voldemort" etc, etc. We know there are quite a few solutions out there, and I'm sure that the strength of the ecosystem plays a large part in what the correct choice is. Do you cover the topic of choosing a NoSQL solutions, and argue the case for why Hadoop is the correct choice, or is the book targeted at people who have already made that decision.
Thanks for your time and knowledge!
David