Business intelligence startup Looker Data Sciences Inc. is tapping into Hadoop’s processing power for data analytics with a new update that provides support for Presto and Spark SQL.

Santa Cruz, CA-based Looker’s platform is described by the company as a “browser-based development environment for business intelligence”. The platform is built atop of Looker’s proprietary programming language LookML, and allows enterprises to describe, define and analyze their data where it resides, as opposed to shifting data to a data warehouse first. The addition of Presto and Spark SQL expands the list of databases Looker is compatible with. Other supported databases include Amazon Redshift, Amazon Elastic MapReduce, Teradata Aster, HP Vertica, Greenplum, Impala, Bigquery and Apache Spark.

Looker’s query execution framework differs from other business intelligence platforms in that it doesn’t need to carry out requests directly; instead, it passes on those requests to the system in which the target data resides. Looker’s product executive Colin Zima appeared on SiliconANGLE’s TV show theCUBE at last year’s HP Big Data event, where he told host John Furrier that the biggest advantage of localized data analysis is that it allows enterprises to exploit the advanced capabilities of modern databases while removing the need to migrate files, significantly speeding up analytics’ tasks.

Now, with the addition of support for Presto and Spark SQL, Looker’s advanced data analysis capabilities are extended to data housed in Hadoop. The platform can “easily transform raw data into meaningful metrics” giving business decision makers the ability to rapidly tap into the previously hard-to-access data stored in Hadoop.

“With Looker on Hadoop, data analysts can create a single source of truth for the entire enterprise, so every business team can quickly ask and answer their own questions,” said Frank Bien, CEO at Looker. “Now all decision-makers, not just a handful of data scientists, can utilize the valuable data in Hadoop to drive better business decisions.”

In a blog post, Bien said as innovative as Hadoop was for storing data, the Hadoop ecosystem was not ready to do business analytics—meaning fast, interactive business analysis and exploration of enormous quantities of data. He noted that vendors that jumped in early had to build complicated systems that transformed, moved, cubed and generally “messed” with the data in Hadoop. As a result, he argues that even after all that, none of the solutions allowed for the speed and repeatability that’s necessary for business analytics to be truly valuable.

The addition of support for Presto and Spark SQL comes at a time when Looker is experiencing sustained growth. The company, which last month bagged a $48 million funding round led by Kleiner Perkins Caufield & Byers (KPCB), claims that it’s revenue base quadrupled over the last year thanks to the addition of 300 new customers, including tech giants like Intel, PayPal Holdings Inc., and Yahoo Inc.