Cloudera Named a Leader in the 2022 Gartner® Magic Quadrant™ for Cloud Database Management Systems (DBMS)

We are pleased to announce that Cloudera has been named a Leader in the 2022 Gartner® Magic Quadrant for Cloud Database Management Systems. Cloudera has been recognized in this cloud DBMS report since its inception in 2020. This year we’ve been named a Leader. This validates our significant momentum in global enterprises. And together, with our recent recognition in the Gartner Peer Insights Customer Choice Distinction for Cloud DBMS, cements our position as an industry leader.

We’re proud to be recognized for the data management and data analytics innovations we have delivered in the new Cloudera Data Platform (CDP). The latest version of CDP represents a major milestone and a bold step forward for our mission. Cloudera has always been in the forefront of disruptive technical innovation in data platforms. We make the data tools people need to confidently tackle the toughest data challenges. In other words, Cloudera makes hard data problems easier. We did it a decade ago when data was big and servers were expensive. We do it today when data is even bigger, and hybridand cloudsare expensive.

Only Cloudera delivers the hybrid and multi-cloud flexibility enterprises need today. We hear it from our customers and industry experts. For example, Gartner has provided very pointed guidance on the urgency and inevitability of hybrid and multi-cloud for data management. Only Cloudera has delivered a solution. 

There are six key capabilities that cement our leadership in enterprise data platforms:

1-Hybrid and multi-cloud portability and scale to support the most demanding workloads. This is unique. Most other cloud DBMS vendors only work in the cloud. Anything else requires integration, sometimes between multiple vendors, which means complexity and risk.

Instead, Cloudera enables the same data services running on private and public clouds with replication capabilities, so companies can easily move workloads when needed. This is a strength, reflected in our 5.0 score on this in the associated Gartner Critical Capabilities for Analytical Use Cases. Cloudera’s platform enables teams to burst compute intensive machine learning workloads to the cloud. Notably, these same services simplify repatriating data workloads back to private clouds, to save on cloud infrastructure expenses. That’s game-changing for performance, budgets, and business continuity. Cloudera is closely partnered with the leading cloud service providers (CSPs), and has optimized our platform and services to run as efficiently on their infrastructure services as possible. This strong focus on multi-cloud and hybrid is essential for our enterprise customers.

2-A truly open data lakehouse. Cloudera has long had the capabilities of a data lakehouse, if not the label. Cloudera enables an open data lakehouse architecture that combines all the flexibility of the data lake with the performance of the data warehouse, so enterprises can use all databoth structured and unstructured. The integration of Apache Iceberg as a native table format in CDP enables customers to build one single data layer for all their workloads without ever moving their data or creating unnecessary silos. It eliminates ETL overhead, while increasing the usability of the data.

3-Streamlined deployment of complex, multi-function workloads. Enterprises run thousands of different workloads on Cloudera. Our open, interoperable platform is deployed easily in all data ecosystems, and includes unique security and governance capabilities. Many of our customers use multiple solutions—but want to consolidate data security, governance, lineage, and metadata management, so that they don’t have to work with multiple vendors. CDP provides integrated governance, in the form of our unique Shared Data Experience (SDX)—specifically highlighted in the recent Gartner report as a strength.

4-Ready for modern data fabric architectures. Cloudera’s investments in SDX are far ahead of the industry standards. We have been investing in development for years to deliver common security, governance, and metadata management across the entire data layer with capabilities to mask data, provide fine grained access, and deliver a single data catalog to view all data across the enterprise. This helps our customers quickly implement an unified data fabric architecture.

5-Integrated open data collection. This differentiator solves a major technical challenge for data projects. With Cloudera, enterprises can collect all data, and run all data workloads with a single data platform. Our new Universal Data Distribution (UDD) capability, launched earlier this year, can collect data from any source and deliver it to any destination for a scalable data pipeline. UDD works on any source and destination, even outside of Cloudera, making it very easy to integrate varied data sources.

6-Operational efficiency to optimize workload performance and cost. Only Cloudera includes integrated capabilities for the entire data lifecycle; data preparation to advanced analytics; and has automation built into all our data services. Low and no-code features and templates make it easy to get started with streaming and machine learning use cases. ReadyFlow galleries and Applied Machine Learning Prototypes (AMPs) significantly reduce time to value for data flow and ML projects. Our long history in leading MPP architectures means we make the best use of cloud native capabilities—delivering the highest performance at the lowest costs.

At Cloudera, our ultimate goal is to empower customers to transform their businesses by providing better, faster use of data with a hybrid, open, portable, and secure data platform for analytics, streaming, ML, and data management at scale. We are proud to be recognized for our history and leadership.

Get an introduction to the latest version of Cloudera’s Data Platform

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Get a complimentary copy of the Gartner 2022 Magic Quadrant for Cloud DBMS


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David Dichmann
Senior Director Product Management
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Navita Sood
Director Product Marketing, Modern Data Architectures
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