Automatic Labs Turns to Databricks Cloud for Faster Innovation and Dramatic Cost Savings

SAN FRANCISCO, CA--(Marketwired - Feb 12, 2015) - Databricks -- the company founded by the creators of the popular open-source Big Data processing engine Apache Spark with its flagship product, Databricks Cloud -- today announced that Automatic Labs, the company whose mission is to connect all cars on the road to the internet, selected Databricks Cloud as its preferred big-data processing platform. Automatic Labs uses Databricks Cloud to run large and complex workloads in order to explore new product ideas and bring them to market faster, such as custom driving reports, recommendations for users regarding fuel-efficient driving and more.

The Automatic Labs solution is an auto-accessory that plugs into the vehicle and an interactive application that collects structured and unstructured data, such as GPS location and computer-based vehicle information, from its users in order to uncover new patterns and insights related to driver safety. As a result, the company often struggled with overwhelmingly large data sets. After deploying Databricks Cloud on Amazon Web Services (AWS), Automatic Labs realized benefits in the following areas:

• Go-to-Market Timeframe Reduction: By speeding up the interactive exploration of the company's entire data set, the time it took to validate products went from a month to a few days.
• Elimination of DevOps Pain: The company immediately freed up precious data science resources from managing infrastructure to focus on core analytics activities.
• Infrastructure Savings: With the ability to setup and teardown Spark clusters instantly in AWS, the company realized significant monthly savings, up to $10,000 in one month.
  
  

Databricks Cloud combines the power of Spark with a zero-management hosted platform and an initial set of applications built around common workflows to simplify the pain of provisioning a Spark cluster, exploring data, and building data products. Spark is a unified processing engine that eliminates the need to stitch together a disjointed set of tools, and provides support for interactive queries (Spark SQL), streaming data (Spark Streaming), machine learning (MLlib) and graph computation (GraphX) in a single common API across the entire pipeline. Additionally, Databricks Cloud reaps the benefit of the rapid pace of innovation in Spark, the fastest growing Apache project with over 400 contributors.

"Consistent and reliable data exploration is essential for Automatic Labs -- both in the way our product functions and our company is run," said Rob Ferguson, director of engineering at Automatic Labs. "For us, Databricks Cloud is all about speed. The platform's rich and simple tools make our deployment a breeze, and its open-source framework enables us to achieve our full potential from a processing and streaming perspective."

"The goal of Spark and Databricks Cloud is to enable real-time interactive analysis and rich visualization for quick and easy deployment," said Kavitha Mariappan, vice president of marketing at Databricks. "The fact that customers like Automatic Labs are realizing these benefits in an enterprise environment and, most importantly, using those benefits to in turn help drivers be safer, is the best kind of indicator that we're doing a lot right."

Download the Automatics Labs case study here: http://go.databricks.com/customer-case-studies

For more information on Databricks Cloud, visit: https://databricks.com/product

About Databricks:
Databricks was founded by the team that created and continues to drive Apache Spark, the most active open source project in the Big Data ecosystem. Databricks' vision is to dramatically simplify big data processing and free users to focus on turning data into value. Databricks Cloud, a cloud platform built around Apache Spark, delivers on this vision by combining the power of Spark with a zero-management hosted platform and an initial set of applications built around common workflows. Databricks is venture-backed by Andreessen Horowitz and NEA. For more information, visit http://www.databricks.com.