MapR Announces Integration with Google Compute Engine

MapR Technologies will make its distribution for Hadoop available on Google Compute Engine. The combination of the new Google service and the MapR distribution is intended to enable customers to quickly provision large MapR clusters on demand and to take advantage of the scalability of a cloud-based solution.

MapR says it has also demonstrated a significant price/performance breakthrough completing a 1TB TeraSort job in 1 minute 20 seconds. This result was achieved on a Google Compute Engine cluster with 1256 nodes, 1256 disks and 5024 cores at a cost of $16.  This result compares favorably with the existing world record of 1 minute 2 seconds that was set with a physical cluster with more than four times the disks, twice as many cores, 200 more servers, and at a cost of more than $5 million. 

“Off-premise, on-demand computing is an important part of the future for Hadoop,” says John Schroeder, CEO and co-founder of MapR Technologies. “MapR is solidifying that future by partnering with Google and leveraging their cost-effective, high performance and scale-out infrastructure.”

The integration of MapR with Google Compute Engine includes a menu of MapR compute configurations where customers can easily store, manage and analyze large volumes of data cost effectively in the cloud. Customers have the flexibility within Google Compute Engine to pay on demand and quickly and easily spin up 1,000-plus node clusters.

MapR on Google Compute Engine will be available as a free private beta for a select number of customers. Interested customers can learn more and request access and to learn more about the Google Compute Engine, go to