[Beowulf] Interesting POV about Hadoop

Lockwood, Glenn glock at sdsc.edu
Tue Jun 3 08:32:25 PDT 2014

With all due respect to Stonebraker, I found the whole article very silly.

It should be no surprise that the "father of Postgres" would think MapReduce is not useful for anything because "Teradata, IBM, Greenplum, HP Vertica, and Amazon Redshift" do it better... he's saying his position is that a bona fide database will do a better job in handling queries than an emulation layer.  Halt the presses!

"The other 95 percent of the market wants SQL" is a salient point he makes, and this is confirmed by companies like Facebook where >90% of their Hadoop workloads are actually Hive queries.  Perhaps 95% of the market is looking at Hadoop as the wrong tool for the job, which wouldn't surprise me.  

What the article seems to slide past is that not all data fits neatly into column-oriented or graph databases.  Hadoop is all about handling unstructured data, so its real utility lies in ETL, not the analytics part.  It's a complementary capability to all these databases that he's saying are better than MapReduce.  Yes, databases are better at doing database things than non-databases.  The bigger problem is getting data into a structure where they'll fit into those databases, and you often can't just use another database to do that.


On Jun 3, 2014, at 8:20 AM, Prentice Bisbal <prentice.bisbal at rutgers.edu> wrote:

> Interesting opinion on Hadoop:
> “The Google guys have to be just laughing in their beer right now because they invented MapReduce a decade ago to serve the data storage needs of the Google crawl of the Internet… and moved all of that to Big Table,” Stonebraker says. “Why did they do that? Because MapReduce is a batch engine and they wanted their crawl database to be updatable, as they wanted to get Twitter feeds into it, in real time.”
> http://www.datanami.com/2014/04/09/array_databases_the_next_big_thing_in_data_analytics_/
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