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We are excited to announce that Gartner has recognized Databricks as a Leader for a second consecutive year in the 2022 Gartner Magic Quadrant for Cloud Database Management Systems. This year, Gartner evaluated 20 vendors, and we’re honored to be recognized for our Ability to Execute and Completeness of Vision.

A complimentary copy of the report can be downloaded here.

2022 Gartner® Magic Quadrant for Cloud Database Management Systems
2022 Gartner® Magic Quadrant for Cloud Database Management Systems

At Databricks, our customer obsession fuels our innovation and product roadmap, and we’ve been rapidly expanding our Lakehouse Platform. In addition to being named a Leader, we’re thrilled to be recognized in both in Completeness of Vision and Ability to Execute.

Below are the some of the biggest strengths of the Databricks Lakehouse Platform, which we believe contributed to our placement in the Gartner Magic Quadrant:

The data lakehouse architecture

The data lakehouse paradigm introduced by Databricks is the future for modern data teams seeking to build solutions that unify analytics, data engineering, machine learning, and streaming workloads across clouds on one simple, open data platform.

The shift to the data lakehouse architecture has increased as every organization is thinking about data-driven transformation. More than ever, business leaders want to leverage data, analytics and AI to transform their business. But, most organizations struggle because their database management systems are too complex and do not support their goals.

We built the Databricks Lakehouse Platform to tackle the most critical challenges around enterprise data, such as complexity with multitudes of workload-specific tools and technologies, vendor lock-in for proprietary formats, poor interoperability and duplicate efforts across cloud platforms. The most recent innovations on our platform simplify your data, analytics and AI workloads and maintain the kind of flexibility and openness that allows your organization to stay agile as you scale with cost-efficiency in mind.

Many of our customers, from enterprises to startups across the globe, love and trust Databricks. We have over 7,000 global customers across all industries building amazing solutions and delivering business impact with the lakehouse architecture.

  • Columbia Sportswear: The Lakehouse helps process and prepare batch and streaming data at scale more efficiently and reliably achieving a 70% reduction in pipeline creation and 48x faster time to insights.
  • Comcast: The Lakehouse scales processing billions of transactions and terabytes of data every day with 90% reduction in required DevOps resources to manage infrastructure costs and 10x overall reduction in compute costs to process data.
  • Johnson & Johnson: The Lakehouse replaces 35 global data sources, streamlines supply chain management and improves inventory predictability with 140x improvement in data delivery times and 45-50% cost reduction for data engineering workloads.

Built on open source and open standards

The data lakehouse architecture is inherently open, built on a vision of unifying your data ecosystem without proprietary restrictions. This philosophy is part of everything we do to advance and execute on lakehouse. We believe in openness for virtually all portions of our offerings.

The Delta Lake storage format is the open foundation of the lakehouse. Today, Delta Lake is the most widely used storage layer in the world, with over 8 million monthly downloads; growing by 10x in monthly downloads in just one year. We recently announced that Databricks will contribute all features and enhancements it has made to Delta Lake to the Linux Foundation and open source all Delta Lake APIs as part of the Delta Lake 2.0 release. The breadth of the Delta Lake ecosystem makes it flexible and powerful in a wide range of use cases.

Additionally, data sharing has become important in the digital economy as enterprises want to easily and securely exchange data with their customers, partners, suppliers and internal teams to better collaborate and unlock value from that data. To enable this without limitations and lock-in, Delta Sharing provides an open solution to securely share live data from your lakehouse to any computing platform.

Vision for Unity Catalog and Delta Live Tables

Governance, security, and regulatory compliance are critical to any data-driven organization because they help guarantee that all data assets are maintained and managed securely across the enterprise. The Databricks Lakehouse Platform provides several new capabilities that further expand data governance, security, and compliance capabilities.

Unity Catalog offers a unified governance solution for all data, analytics and AI assets, with centralized access and audit controls,  automated lineage for all workloads and  performance and scalability for a lakehouse on any cloud. Unity Catalog is now Generally Available on Azure and AWS.

This year, we also announced general availability on all three clouds of Delta Live Tables (DLT), the first ETL framework to use a simple, declarative approach to building reliable batch and streaming data pipelines. Since its launch earlier this year, Databricks continues to expand DLT with new capabilities.

What’s next

We believe our recognition as a Leader for a second consecutive year and our position in both Completeness of Vision and Ability to Execute is a testament to the success of the lakehouse architecture, and its ability to bring together data teams.

At Databricks, we continue to innovate and push the boundaries of what’s possible. The Lakehouse brings together data leaders and practitioners to execute any data use case – analytics, data engineering, data streaming, data science, MLops and so much more. We thank our customers and partners for being on this journey with us.

Learn more

To learn more about the Databricks Lakehouse Platform, visit our website and check out our sessions and in-depth lakehouse content at our Data+AI World Tour 2022. Also, follow us @Databricks for the latest news and updates.

Read the Gartner Magic Quadrants for Cloud Database Management Systems and Data Science and Machine Learning Platforms to learn more.

Read the Reports!

Gartner, Magic Quadrant forCloud Database Management Systems,Henry Cook, Merv Adrian, Rick Greenwald, Xingyu Gu, 13 December 2022.

GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally, and MAGIC QUADRANT is a registered trademark of Gartner, Inc. and/or its affiliates and are used herein with permission. All rights reserved.Gartner does not endorse any vendor, product or service depicted in its research publications, and does not advise technology users to select only those vendors with the highest ratings or other designation. Gartner research publications consist of the opinions of Gartner’s research organization and should not be construed as statements of fact. Gartner disclaims all warranties, expressed or implied, with respect to this research, including any warranties of merchantability or fitness for a particular purpose.

This graphic was published by Gartner, Inc. as part of a larger research document and should be evaluated in the context of the entire document. The Gartner document is available upon request from Databricks.

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