|By Jnan Dash||
|January 11, 2014 12:38 PM EST||
In the scientific community, HPC was used for meteorology (weather simulation) and for solving engineering equations. Hadoop is used more for discovery and pattern matching. The underlying technology is similar: clustering, parallel processing and distributed file systems. Hadoop addresses the “volume” aspect of Big Data, mostly for offline analytics.
NoSQL products such as MongoDB address the “variety” aspect of Big Data: how to represent different data types efficiently with humongous read/write scalability and high availability for transactional systems operating in real time. The existing RDBMS solutions are inadequate to address this need with their schema rigidity and lack of scale-out solutions at low cost. Therefore, Hadoop and NoSQL are complementary in nature and do not compete at all.
Whether data is in NoSQL or RDBMS databases, Hadoop clusters are required for batch analytics (using its distributed file system and Map/Reduce computing algorithm). Several Hadoop solutions such as Cloudera’s Impala or Hortonworks’ Stinger, are introducing high-performance SQL interfaces for easy query processing.
Hadoop’s low cost and high efficiency has made it very popular. As an example, Sears’ process for analyzing marketing campaigns for loyalty club members used to take six weeks on mainframe, Teradata and SAS servers. The new process running on Hadoop can be completed weekly.
The Hadoop systems, at 200TB, cost about one-third of 200TB relational platforms. Mainframe costs have been reduced by more than US$500,000 per year while delivering 50x to 100x better performance on batch jobs. The volume of data on Hadoop is currently at 2PB. Sears uses Datameer, a spreadsheet-style tool that supports data exploration and visualization directly on Hadoop. It claims to develop interactive reports in three days, a process that use to take six to 12 weeks.
With RDBMS, there was impedance mismatch when an object-oriented programming model had to map to the row-column structure of the database (like translating Swahili to French). The rich data model can handle varieties of data with full indexing and ad hoc query capabilities.
The other reason is its ability to scale horizontally over commodity servers and provide massively parallel processing. This aspect is similar to Hadoop’s distributed architecture. However, NoSQL has to deal with the operational aspects of production databases running on premise or in the cloud, whereas Hadoop basically operates in offline batch mode for analysis.
NoSQL is used by large enterprises to build “systems of engagement.” Enterprise IT has spent decades building “systems of record” to run their business—essentially technology that contains a database. Now, CIOs are under pressure to build systems of engagement in which the focus is on using modern technology and the Internet to better communicate internally and externally.
One such system of engagement was recently built at MetLife, the 145-year old insurance company. The goal was to provide a 360-degree view of the customer (switching from a policy-centric view to a customer-centric view), whose information was scattered across 20 legacy systems of record. This way, any agent at MetLife can get a complete picture of a customer’s activities using a mobile device, anytime, from anywhere.
A critical component of any IoT project is what to do with all the data being generated. This data needs to be captured, processed, structured, and stored in a way to facilitate different kinds of queries. Traditional data warehouse and analytical systems are mature technologies that can be used to handle certain kinds of queries, but they are not always well suited to many problems, particularly when there is a need for real-time insights.
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You think you know what’s in your data. But do you? Most organizations are now aware of the business intelligence represented by their data. Data science stands to take this to a level you never thought of – literally. The techniques of data science, when used with the capabilities of Big Data technologies, can make connections you had not yet imagined, helping you discover new insights and ask new questions of your data. In his session at @ThingsExpo, Sarbjit Sarkaria, data science team lead ...
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SYS-CON Events announced today that Catchpoint, a leading digital experience intelligence company, has been named “Silver Sponsor” of SYS-CON's 20th International Cloud Expo®, which will take place on June 6-8, 2017, at the Javits Center in New York City, NY. Catchpoint Systems is a leading Digital Performance Analytics company that provides unparalleled insight into your customer-critical services to help you consistently deliver an amazing customer experience. Designed for digital business, C...
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Jan. 19, 2017 01:15 PM EST Reads: 5,688
The 20th International Cloud Expo has announced that its Call for Papers is open. Cloud Expo, to be held June 6-8, 2017, at the Javits Center in New York City, brings together Cloud Computing, Big Data, Internet of Things, DevOps, Containers, Microservices and WebRTC to one location. With cloud computing driving a higher percentage of enterprise IT budgets every year, it becomes increasingly important to plant your flag in this fast-expanding business opportunity. Submit your speaking proposal ...
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