Big Data Versus Data Warehouse: Only One Will Survive

Big Data will continue to dominate 2013 headlines – along with BYOD, mobility, NoSQL, Dell privatization, HP reorganization and Apple Anything – but it’s time in the sun is strictly limited. According to Gartner’s new Magic Quadrant for Data Warehouse Database Management Systems, “Big Data” concepts will become part of the “new normal” in analytics and data management and integration, but will cease to be a distinguishable technological approach in 2015 and will be wholly obscured by 2018.

However, for now, Big Data remains a specific requirement that the data warehouse must address as it evolves into a new form, the logical data warehouse, and will generate $232 billion in IT spending through 2016, said Gartner. The fundamental requirements for the data warehouse haven’t changed significantly, and nothing out there says it is going to change, said Tasso Argyros, co-president of Teradata Aster. Teradata, which bought Aster Data in 2011 to enhance its unstructured data capabilities, was in the leaders’ quadrant of the GMQ for the 14th consecutive year, joining the likes of Oracle, SAP, Microsoft, IBM and EMC, and has been in the data warehouse business for the last 30 years.

“Teradata has been the leader in data warehousing,” said Argyros. Big Data is all about the need for more analytics, and that’s just another opportunity for the company, he said.

During the 1990s, IT was all about infrastructure to capture a lot of data. In the 2000s, the focus was on structured data and analysis. Now we realize there’s a lot more data not being captured and analyzed, data that can be used to improve business and business metrics, he said.

That’s what created Big Data, and where Teradata saw an opportunity with unstructured data, said Argyros. “That’s why Teradata bought Aster Data in 2011, where I was the founder.”

In October the company launched a new version of its Big Analytics Appliance based on the Aster hybrid row/column parallel database. However, while the hardware was significant, what Teradata really wanted to talk about is how its software is integrating the disparate Aster, Teradata, and Hadoop platforms together into a big data masher and muncher. The idea is to use Hadoop to capture, store, and refine incoming unstructured data (telemetry from web sites and retail sites and third party data sources) and then have that data accessible for crunching alongside operational data in the Aster and Teradata databases. Aster is where you find the useful nuggets using intense analytics, and Teradata is where you do the ba-zillions of operational queries you need to run the biz.

If Big Data is destined to disappear, it’s not going quietly, and the disruption to the DBMS market appears to be more than the blip Argyros suggests. As Big Data analytics shifts from batch to real-time, from a nice-to-have to a must-have, the delivery of complex analytics results in as short a time as possible will gain in desirability, wrote Evan Quinn, Senior Principal Analyst, Enterprise Strategy, in a new blog.

‘Therefore, ESG believes that the database primarily designed for analytics will increase the gap over more general use-case databases. Those MPP and graph analytics databases, at least in the enterprise, will gain share in 2013.’

Quinn noted that given all the databases out there for Big Data analytics, whether on-premises, on-appliance, or in-cloud, ESG believes the market is quite saturated, and certainly confusing for the overwhelmed enterprise DBA trying to support big data projects. ‘Therefore 2013 is the year for MISO, and we would include Teradata Aster and EMC Greenplum in this mix, to provide comfort and assurance that the DBA can stick with her/his established provider and not sacrifice the state-of-the-art by doing so.’

Earlier this month Teradata reported a 10% increase in fourth quarter revenue, and a 13% increase for the year to $2.6 billion, and non-GAAP earnings per share increased 23% over 2011. The company released its Unified Data Architecture (UDA) in October to help companies build out their data architectures and eliminate the confusion around Big Data, said CEO Michael Koehler.

“The Teradata Unified Data Architecture or UDA helps companies build out their data architectures and eliminate the confusion,” he said during an analyst’s call to discuss the financial results. “The key components are: Hadoop with its ability to ingest, transform and store big data in a very economical manner; Aster, as a discovery platform for Hadoop; and workload specific data warehouses for strategic and mission-critical analytics for companies to run a business.”

Gartner cautions that while there is change transforming this market, for most of the past 20 years, fewer than 20% of organizations have tended to adopt visionary architectures five to seven years before they became widely accepted. ‘In 2012, however, the emergence of the logical data warehouse — and its associated set of best practices for warehousing and analytics data management — had a significant impact on customers’ vision.’

One alternative to the logical data warehouse as an analytics information architecture is wholesale replacement of the data warehouse with search, content analytics and MapReduce clusters, and the elimination of the centralized repository, said the research company. The concept of cloud-deployed analytics data management (sometimes referred to as data warehouses, sometimes contrasted with them), also gained momentum in 2012.

Regardless of Big Data’s future, and despite the growing interest in NoSQL, one thing that won’t change is the need for the venerable SQL database, said Argyros. “The big thing people don’t understand is that Big Data is a big SQL opportunity. Sometimes people get confused that people don’t want SQL anymore. I think there will be a lot more SQL.”


Author: Steve Wexler

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