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Hadoop is better with Big SQL from IBM

Hadoop is a great technology for analyzing huge amounts of data. Hadoop can be hard to use. Big SQL brings the power of SQL to Hadoop. It lets you leverage your SQL skills and your JDBC and ODBC applications with data stored in HDFS and HBase.
by Leon Katsnelson on 18 April 2013

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Transcript of Hadoop is better with Big SQL from IBM

from IBM Hadoop's much better with Big SQL Hadoop is GREAT! Hadoop truly is GREAT! Look at all the data it can chew through! you need a bunch of guys in lab coats to make use of it
you have to know Java and write these strange MapReduce programs
the tools you used for years with data in SQL databases ... they are not likely to work in Hadoop world ... Except Hive is good .... but not good enough
HiveQL is "SQL-like" but not really SQL
Hive data types are very limited, and
Many SQL applications can't use Hive
Hive can be quite slow. Hive is OK for long running batch jobs ... but you need something else for interactive queries. but wait, what about Hive? That's exactly what Big SQL from IBM is for:
use real SQL not "SQL-like"
support for data types you need
connect existing JDBC and ODBC applications to slice and dice data stored in Hadoop

Bonus: Big SQL is smart enough to optimize your queries for fast execution just like relational databases do Wouldn't it be nice if we could use Hadoop as if it was a relational database?! ... and with Big SQL, anyone can use it http://bigsql.imdemocloud.com IBM Big SQL
is SELECT * from Hadoop Big SQL works nicely with whatever those guys in lab coats do with MapReduce.
It uses the same scheduler and the same catalog.
You access the same data either Hadoop-way or with SQL.

Big SQL lets you work with Hadoop as if it was a relational database ... without changing Hadoop. see it for yourself :
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