Noodling on NoSQL: Thoughts on Multi-Structured Data Management
OCT 15, 2013 4:09pm ET

Related Links

Ellison Becomes Oracle Chairman as Catz, Hurd Split CEO Job
September 18, 2014
Stop Governing Your Data - Start Leading Data Behaviors and Outcomes
September 18, 2014
Big Data Gets Bigger Footprint in Insurance
September 16, 2014

Web Seminars

Why Data Virtualization Can Save the Data Warehouse
Available On Demand
Essential Guide to Using Data Virtualization for Big Data Analytics
September 24, 2014

Bringing SQL to NoSQL: Future or Fool's Errand?


One of the more interesting concepts recently in the world of NoSQL is the push to bring SQL access to flexible multi-structured data sets in NoSQL data management systems or, more simply, put SQL on Hadoop, to give a specific example. Some consider this to be the next great evolution in the future of NoSQL platforms. Some consider it to be a fool's errand to attempt.

Get access to this article and thousands more...

All Information Management articles are archived after 7 days. REGISTER NOW for unlimited access to all recently archived articles, as well as thousands of searchable stories. Registered Members also gain access to:

  • Full access to including all searchable archived content
  • Exclusive E-Newsletters delivering the latest headlines to your inbox
  • Access to White Papers, Web Seminars, and Blog Discussions
  • Discounts to upcoming conferences & events
  • Uninterrupted access to all sponsored content, and MORE!

Already Registered?


Comments (2)
SQL was designed to access data in flat, atomic, degenerate tables. It's been successful in that realm, but NoSQL is an alternate universe, maybe even multiple alternate universes, where alternate languages are required to express the richer, more complex relationships in the data.

Welding SQL access onto NoSQL data sources is a first, baby step, but it will always be a mere toe-dip into the new waters. Or it should be. The danger is that, because SQL is so entrenched in an entire generation of data handlers that its use will impede the creation of the new, better data analytical languages that are required.

Posted by Chris G | Friday, October 18 2013 at 9:02AM ET
Hi John, There is a place for structured, as well as unstructured data. Completely agree with the statement "store structured data in multi-structured environments much more easily". I would split the MongoDB/Cassandra technologies from the Hadoop technologies. The MongoDB/Cassandra core differentiation is predictable puts/gets of individual records at scale. Hadoop core differentiation is robust batch processing at scale.

SQL isn't needed for put/gets of individual records, but is likely useful for a subset of the Hadoop operations, especially if they can deliver differential latency and connectivity to existing graphical tools.

SQL created as the ONLY access layer on top of next gen data management tools would be limiting, but NoSQL + SQL is clearly more useful than either access method alone.

Cheers, Jim Tommaney CTO, Calpont

Posted by Jim T | Friday, October 18 2013 at 2:31PM ET
Add Your Comments:
You must be registered to post a comment.
Not Registered?
You must be registered to post a comment. Click here to register.
Already registered? Log in here
Please note you must now log in with your email address and password.
Login  |  My Account  |  White Papers  |  Web Seminars  |  Events |  Newsletters |  eBooks
Please note you must now log in with your email address and password.