Databricks Raises $250 Million in Series E Funding to Boost its Data Analytics Platform

By StartUp City | Friday, April 05, 2019

Databricks, a San Francisco, CA-based data analytics company secures $250 million in series E funding round to expand its engineering development team, bolster its EMEA and APAC market presence, and improve customer support in financial services, healthcare, retail, the public sector, and various other industries. The investment round led by Andreessen Horowitz (a16z) had participation from Coatue Management, Microsoft, and New Enterprise Associates (NEA).

The new financing brings the total funding of Databricks to $498.5 million with a total valuation reaching $2.75 billion. Databricks offers a unified analytics platform that helps enterprises process, integrate and analyze troves of data in a speedy manner. The platform also enables data science teams, to collaborate with data engineering and lines of business to build data products. Databricks’ unified platform is based on Apache Spark, which is an open-source, distributed, and a cluster-computing network that allows enterprises to create connections across various siloed data storage systems.  Databricks also provides a fully managed, scalable, and secure cloud infrastructure that reduces the operational complexity and total cost of ownership, making it easier for business to manage their data. The unified platform of the company helped Microsoft to help its cloud customers quickly parse large amounts of data. Databricks also offers multiple features and solutions which are based around Microsoft Azure and Amazon Web Service (AWS).

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Databricks is a data analytics company that was founded in 2013 by the creators of Apache Spark. The company’s Unified analytics platform integrates data science and engineering across the Machine Learning lifecycle from data preparation to experimentation and deployment of ML applications. The company provides solutions for cybersecurity analytics, deep learning, GDPR, Internet of Things (IoT), machine learning and graph processing, and many others.

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