"The place that enterprises will store their data is shifting toward Hadoop," Olson told InformationWeek last week in a preview of the speech. "We're seeing customers not replace, but, rather, rationalize their enterprise data warehouse investments by adding Hadoop alongside."
Olson also announced a new Cloudera Search capability built on Apache Solr, but the larger purpose of the presentation was to question assumptions about enterprise data management. EDWs are "increasingly costly and difficult to maintain," Olson said, because the volume and variety of data now encountered is "totally out of whack" with what relational data warehouses were designed to handle in the 1990s.
EDW costs are upward of $20,000 per terabyte, versus $1,000 to $2,000 per terabyte for Hadoop clusters, including hardware, according to Olson. Thus the time is right, he said, to reconsider where most data is stored, transformed, cleaned, prepared and interactively queried.
[ Want more on changes in data management? Read Big Data Debate: Will Hadoop Become Dominant Platform? ]
"All of those workloads are sucking cycles away from the stuff that the EDW platform does very well," Olson said, citing high-powered analytics and cube-based analyses as the key roles that EDWs will continue to handle.
The announcement of Cloudera Search expands the list of Hadoop platform capabilities. Tapping the open-source Apache Solr search engine, Cloudera said it will support natural language keyword searches and faceted navigation of data stored in the Hadoop Distributed File System (HDFS) and Apache HBase. The tool runs on the Hadoop cluster and will be useful for exploring data and finding subsets of information that might be targeted for large-scale MapReduce processing, Olson said.
"When you have petabytes of data, folders don't work anymore, and we've all learned from Google that, when you need to find some bit of information, you just go search for it," he said. "Anybody can use this and you don't need to define ontologies or taxonomies to set it up."
Cloudera Search has been in private beta for several months, with Monsanto cited as a company using the software to support a high-scale search application. The software will be distributed as part of Cloudera's Hadoop distribution, but management capabilities for search will be an add-on offering that's part of the vendor's commercial Cloudera Manager software.
Cloudera competitor MapR recently announced its own answer to search-on-Hadoop, also based on Solr, but Olson discounted it as "an announcement not supported by shipping code." Cloudera Search is now available for download as part of a public beta test that's expected to last three months.
As for Cloudera's premise of offloading ETL and basic BI workloads and data volumes from more expensive EDWs onto Hadoop, the idea is not shocking or new. The strategy of turning Hadoop into the enterprise data hub has been articulated by outspoken practitioners such as Phil Shelley, CTO at Sears Holdings.
The topic also has been openly debated by vendors, with leading database suppliers such as Teradata and IBM shrugging off Hadoop as just one more arrow in the data-management quiver that enterprises will need to address big-data opportunities.
With the costs of Hadoop what they are and the scale of data growing exponentially, there's little doubt that Hadoop's popularity will grow. Time will tell just how soon and to what extent it will displace EDWs from accustomed roles such as transforming and storing the bulk of historical data and supporting the basics of BI and reporting.
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