The Hadapt approach to making Big Data consumable | #BigDataNYC
Harnessing the power of Big Data is no small feat, requiring organizational commitment, substantial investments in infrastructure and talent and clear project objectives. There’s also the matter of putting that power in the hands of users, a challenge that Hadapt has set out to solve. Based in Cambridge, Massachusetts, the startup offers a relational abstraction layer for Hadoop that lets analysts unlock the value of their data without having to go through Hive.
Hadapt engineering head Christopher Rocca and pre-sales manager Patrick Toole dropped by theCUBE at SiliconANGLE’s Big Data NYC 2013 gathering to discuss how their firm makes information more consumable. The company’s software provides access to data in HDFS via SQL rather than MapReduce or Java, which are more complex and not as common among everyday business users.
According to Toole, Hadapt bridges the data knowledge gaps that plague traditional enterprises by eliminating the need for complex ETL processes. The company helps customers unify their analytics environments, abstract management and set clear goals for delivering actionable insights.
Asked about the differentiators that set Hadapt apart from Cloudera Impala, a rivaling SQL-on-Hadoop solution, Rocca says that his firm’s software is smarter and more agile.
“Our fundamental architecture allows us to scale very wide, push queries down to the data nodes, get a lot of parallelism out of the cluster [and] deal with very large datasets not limited to any kind of memory scaling issue,” Rocca elaborates. “You want to not just have basic SQL operations on normalized data, you really want a more flexible analytics platform where you can start to bring in data from some other sources,” specifically clickstream information and other unnormalized workloads.
Toole adds that Hadapt provides value beyond this core functionality with machine learning algorithms and a flexible schema that can process both structured data and multi-structured information such as text and key-value pairs.
See the full interview for more details about Hadapt’s role in the Big Data ecosystem.
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