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January 31, 2019

Databricks Named a Visionary in Gartner Magic Quadrant for Data Science and ML Platforms

SAN FRANCISCO, Jan. 31, 2019 — Databricks, a leader in unified analytics and founded by the original creators of Apache Spark, has been recognized as a Visionary in Gartner’s January 2019 Magic Quadrant for Data Science and Machine Learning Platforms. Databricks’ Unified Analytics Platform makes artificial intelligence (AI) much more achievable for enterprise organizations and enables them to accelerate their AI initiatives. Databricks will showcase its Unified Analytics Platform at the Gartner Data & Analytics Summit 2019 taking place March 18 – 21 in Orlando, FL.

“We’re thrilled to see Databricks recognized as a Visionary in the latest Gartner Magic Quadrant focused on data science and machine learning. This is the second consecutive year Databricks has been recognized as a Visionary in this report,” said Bharath Gowda, vice president of Product Marketing at Databricks. “We believe our positioning in this report validates our singular focus on eliminating the silos between data engineering and data science through unified analytics.”

Unified Analytics combines data processing and machine learning in a single collaborative platform for data science and engineering teams. The founders of Databricks originally created Apache Spark as the first unified analytics engine, which introduced this new class of software. Databricks’ Unified Analytics Platform is a cloud-based platform powered by Apache Spark that provides auto-scaling for big data clusters, performs up to 50x faster than Apache Spark, integrates seamlessly with machine learning frameworks and simplifies productionizing data pipelines.

Hundreds of global organizations such as Nielsen,, Overstock, Bechtel, Shell and HP are leveraging Databricks to unify data science and data engineering teams across the end-to-end data and machine learning lifecycle. Attendees of the Gartner Data & Analytics Summit can hear their peers’ real-world experiences with Databricks’ Unified Analytics Platform as well as have a hands-on experience by visiting the Databricks booth.

Gartner’s report evaluated 17 vendors based on their ability to execute and the completeness of their vision for its Magic Quadrant for Data Science and Machine Learning Platforms. Gartner’s completeness of vision axis comprised seven evaluation criteria: market understanding, marketing strategy, sales strategy, offering (product) strategy, business model, vertical/industry strategy, innovation, and geographic strategy. The completeness of vision axis comprised seven criteria: product or service, overall viability (financials), sales execution/pricing, market responsiveness/record, marketing execution, customer experience, and operations.

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Source: Databricks

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