|By Jnan Dash||
|April 3, 2014 08:41 PM EDT||
I was invited to speak at a Oracle NoSQL and Big Data Meetup last night. Here is the link for the event. I kicked it off with a broad picture of the Big data landscape trying to clear some confusions on varieties of terms – NoSQL, NewSQL, Data Warehousing Appliances, data exhaust, M2M, Hadoop, data visualization, machine learning, etc. Then Dave Rubin from Oracle presented their latest release of Oracle NoSQL 3.0 that was announced this week. Oracle acquired Sleepycat which was the keeper of BerkleyDB, the key-value store that originated at the UC, Berkeley during the 1990s. Mike Olson who founded Cloudera was one of the key developers. Then I presented MongoDB Momentum showing seven examples of actual customer usage of MongoDB to solve business problems.
Oracle’s new release adds a tabular model on top of the key-value store. It also added secondary indexing, a shard key, and several operational features. It is not surprising to see the push to view tables in line with the Oracle RDBMS. Time will tell how useful that is, as the NoSQL experience is to move away from the two-dimensional row-column view. But it may be a co-existence statement by Oracle to its customer base.
My theme on MongoDB momentum was to highlight the need for Systems of Engagement (something Geoff Moore has been talking about lately) on top of Systems of Record. Geoff says these systems of record were built decades back with an RDBMS at the center. They are like the interstate highway system in the US. Now what we need is to build cool and groovy interactive applications using newer technologies like the web, cloud and mobile devices. These systems must be built very rapidly and must be highly elastic to accommodate new data formats and high scalability with performance. I mentioned several such examples at enterprises like MetLife, Telefonica, Cisco, Intuit, etc. These new-age modern applications are built using MongoDB’s flexible data model and horizontal scale-out architecture to yield fast performance and scale. MongoDB is rapidly growing with over 7 million downloads and thousand plus customers in just 4-5 years of its life.
There were 117 people attending the event and it was quite interactive with lots of questions at the end.
Companies can harness IoT and predictive analytics to sustain business continuity; predict and manage site performance during emergencies; minimize expensive reactive maintenance; and forecast equipment and maintenance budgets and expenditures. Providing cost-effective, uninterrupted service is challenging, particularly for organizations with geographically dispersed operations.
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