In a recent interview with Tech Target, the engineering manager of Komli Media shared his decision-making process to select a big data service. Komli Media is an ad placement agency that uses data based on a potential customer’s past purchases and search history to select which advertisements will be most effective. The company relied on Hadoop to handle the large volumes of data the company collects but found that running Hadoop on-premise was expensive, and the company’s fixed-size clusters couldn’t keep up with processing demands.
In order to keep up with customer demand, Shailesh Garg, Komli engineering manager, determined it was time to look at a managed, scalable solution.
“We needed a solution where we could scale the Hadoop cluster and add machines in a few minutes,” Garg said in the interview. “In today’s world, that solution is a cloud solution.”
Other must-have features Garg was looking for included being cost-effective and easy to use with lightning-fast speeds. Garg looked at several popular big data in the cloud solutions, including Amazon Elastic MapReduce, but he found Amazon EMR still wasn’t processing data fast enough. When he tested Qubole Data Service, on the other hand, he was impressed by the auto-scaling feature and how quickly the system handled the data.
Once Garg settled on using Qubole, the process of migrating to AWS S3 and setting up a data pipeline took a month. With Qubole, Komli Media can now meet clients’ needs in a couple of hours instead of a day and has cut costs by 50%.
Read the full Komli Media Case Study.
