October 01, 2016 8:58 AM ET

Internet Software and Services

Company Overview of Databricks Inc.

Company Overview

Databricks Inc. provides a cloud platform that helps traditional and disruptive organizations to turn data into value. It offers Databricks, a just-in-time data platform that is used for simplifying data integration, real-time experimentation, and robust deployment of production applications for developers and data scientists. The company’s Databricks is a cloud-based data processing platform to solve complex data problems securely. It serves advertising and marketing technology, energy and utilities, enterprise technology software, financial and insurance, healthcare and pharma, Internet of Things (IoT), manufacturing and industrial, media and entertainment, public sector, retail and consum...

160 Spear Street

13th Floor

San Francisco, CA 94105

United States

Founded in 2013



Key Executives for Databricks Inc.

Co-Founder, Chief Executive Officer and Director
Co-Founder and Executive Chairman
Co-Founder, Chief Technology Officer and Director
Co-Founder and Vice President of Engineering
Co-Founder and Vice President of Education
Compensation as of Fiscal Year 2016.

Databricks Inc. Key Developments

Databrick Announces Apache Spark 2.0

Databrick announced that Apache Spark 2.0 is generally available on its just-in-time data platform, making it the first vendor to offer Apache Spark 2.0 support. With major contributions from Databricks and the Spark community, this is the first major release of open source Spark since Spark 1.6 in 2015. Databricks customers can now immediately benefit from Spark 2.0's three core attributes -- easier, faster, and smarter. Among other major improvements as outlined in the Databricks blog post, the most notable features of Apache Spark 2.0 are: Speed: Gaining huge performance in orders of 5 to 10 times faster than Spark 1.6 for some Spark operators due to Tungsten's Phase 2 whole-stage-code generation and Catalyst's code optimization; Simplicity: Unifying developer APIs across Spark's libraries such as DataFrames and Datasets; Structured Streaming: Laying the foundation for continuous applications by providing high-level declarative streaming APIs based on DataFrames and Datasets built atop Spark SQL engine that works on real-time data; Machine Learning Model Persistence: Saving and loading pipelines and models across all programming languages supported by Spark; DataFrame-based Machine Learning APIs: Emerging as the primary MLlib package with its "pipeline" APIs and focusing future developments on DataFrame-based API; Standard SQL Support: Expanding Spark's SQL capabilities for SQL:2003 features, introducing new ANSI SQL parser, and supporting scalar and predicate type subqueries. For Databricks users, immediate access to Apache Spark 2.0 to create new clusters is as simple as selecting the release from its menu -- all completed with a few clicks. Spark 2.0 is highly compatible with Spark 1.6, so migrating code should require minimal effort. By making Spark 2.0 instantly accessible within a fully managed data platform, Databricks affords its users a full suite of tools to harness the open source 2.0 release advancements and ensure end-to-end security, giving data scientists and data engineers the easiest way to analyze data, perform advanced analytics, and deploy Spark applications. The Apache Spark 2.0 features are available and supported for all Databricks customers.

Edmunds.com Leverages Databricks to Improve Vehicle Data Quality and Customer Experience

Databricks announced that Edmunds.com has implemented Databricks to improve the overall customer experience of their website. Accurate vehicle data is of the utmost importance for Edmunds' website visitors. The data team at Edmunds integrates a wide spectrum of data, ranging from their proprietary data sets to paid data sources, to automatically populated details of each vehicle from its VIN code. The rapid growth in the volume and complexity of vehicle data created enormous challenges in maintaining data integrity. For example, determining the percentage of Subarus with missing option details or Hondas with incorrect exterior color were problems that the Edmunds engineering team spent hours trying to fix. While Edmunds evaluated Apache Spark as a solution to its data challenges, the company also determined that its analysts and data professionals needed a comprehensive data platform that provided managed services to simplify its Spark deployment and increase productivity. With the implementation of Databricks, Edmunds was able to democratize data access across its organization, allowing its data engineering, data science, and business analyst teams to work collaboratively on their data at scale. Edmunds also achieved the following quantitative results: Accelerated ad hoc data exploration and analysis by six-fold allowing the company to answer data integrity questions faster; Improved reporting speed by reducing processing time by 60%, or an average of 3-5 hours per week for the engineering team; Improved vehicle data quality metrics across its website by 35%.

Databricks Launches Just-In-Time Apache Spark Platform on Amazon Web Services GovCloud (US) to Meet Strict US Government Compliance Requirements

Databricks announced that its just-in-time platform is now available on Amazon Web Services (AWS) GovCloud (US), an isolated AWS region designed to host sensitive data and regulated workloads in the cloud. AWS GovCloud (US) helps U.S. Government agencies and customers migrate sensitive data in the cloud by addressing their specific regulatory and strict compliance requirements, such as the U.S. International Traffic in Arms Regulations (ITAR), FedRAMP, and DoD SRG Level 3 requirement. With this launch, Databricks becomes the first and only fully-managed just-in-time Apache Spark platform on AWS GovCloud (US). From patent approvals to econometrics, government agencies rely on efficient data processing and analysis to carry out their duties. The explosion of data volume, variety and velocity has created enormous challenges in meeting the data analytics need. Agencies using Databricks on AWS GovCloud (US) will be empowered to build and deploy advanced analytics solutions in a secure cloud environment under the protection of the Databricks Enterprise Security (DBES) framework, which seamlessly combines encryption, integrated identity management, role-based access control, data governance, and compliance standards to secure Apache Spark workloads end-to-end. Databricks is also available in nine AWS regions globally in addition to AWS GovCloud (US).

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