Dremio celebrates its commitment and contributions to Apache Polaris
Dremio, the intelligent lakehouse platform, today announced that it is acknowledging and celebrating the one-year anniversary of Apache Polaris, and is solidifying its allegiance to the project that has quickly transformed how organizations manage data at scale. Built specifically for modern data architectures, Polaris is an open-source metadata catalog designed to simplify the management of Apache Iceberg tables across diverse engines and cloud environments. Polaris centralizes metadata management, enabling seamless interoperability across multiple engines while ensuring AI readiness. This approach empowers organizations to modernize their data architectures flexibly, free from the constraints of proprietary, vendor-specific solutions.
Since its inception one year ago, Polaris has seen rapid growth by reaching over 1,500 stars and 244 forks on GitHub, reflecting its growing community and recognition as a key open-source project. Dremio has been at the forefront of Polaris’ success, contributing significantly to its development and future capabilities, including the stabilization of the Polaris runtime, integration of the Iceberg-catalog-migrator, and enhancements to build, CI, and testing processes. Dremio’s enterprise offerings are built on Polaris and help organizations maximize the potential of their data lakehouses while ensuring they stay independent from proprietary vendor ecosystems.
Over the past year, Dremio has made substantial contributions to Apache Polaris, including:
- Stabilization of the Polaris runtime with the integration of the Quarkus runtime.
- Contributing a framework for running benchmarks in Polaris (available here).
- Donating the Iceberg-catalog-migrator from Nessie to Polaris, enhancing the project’s capabilities.
- Improving Build, CI, and test processes, ensuring a more robust development cycle.
- Enhancements to Helm charts, improving deployment flexibility and scalability.
Polaris is a powerful tool that centralizes metadata across diverse engines, ensuring consistency, accessibility, and governance for Iceberg tables. Without a robust catalog, it becomes impossible to manage large-scale, distributed data environments. Polaris solves this problem by decoupling metadata from storage, which allows teams to manage data at scale with fine-grained access control, transactional consistency, and enhanced security—all while retaining the flexibility to work with different engines and cloud providers.
“As organizations continue to expand their use of data lakehouses, the need for an effective, scalable metadata management solution is critical,” said Alex Merced, Head of Developer Relations at Dremio. “The Apache Iceberg REST Specification allows for portability of Iceberg tables across engines. As Apache Polaris continues to become the community standard catalog implementation, then access controls can become portable across the ecosystem as well,”
Dremio continues to drive Polaris forward with several initiatives currently in process which include:
- NoSQL Persistence to broaden the project’s use cases.
- Browser UI development, improving user interaction with Polaris.
- External IDP support, further expanding the flexibility of Polaris integrations.
“We are extremely proud of Dremio’s contributions to Apache Polaris over the past year. As a key contributor to the podling, we’ve been able to enhance Polaris through technical advancements such as improving the runtime, the build and CI processes, and integrating critical features like the Iceberg-catalog-migrator which help grow the Polaris community” said JB Onofré, Principal Software Engineer at Dremio and Director of the Apache Software Foundation. “These contributions reflect our commitment to open-source innovation and advancing the future of data governance and AI readiness. With new initiatives like NoSQL persistence and browser UI support already in progress, the next year promises even more exciting developments.”
As part of its ongoing commitment to supporting the Apache Polaris community, Dremio is also proud to announce that Alex Merced is authoring the first comprehensive guidebook on Apache Polaris and will be published by O’Reilly. The book will provide in-depth insights into the Polaris architecture and best practices and is expected to be a valuable resource for developers and data teams looking to leverage the power of Polaris in their data management workflows. The early release containing the first several chapters can be accessed here.
The project is positioned to further disrupt the data ecosystem with key updates like centralized policy management, unstructured data support, and catalog federation already in development. These features will significantly enhance interoperability and bridge gaps between different data platforms. As the AI revolution accelerates, Polaris’ ability to unify metadata becomes increasingly critical to driving AI-ready data systems.
According to Gartner®, “Metadata has risen to the highest level of interest and is experiencing aggressive management and analysis that continues into 2025. Data fabric, data mesh, augmented data management, code generation, no-code/low-code, semantic access, governance, and data quality all depend upon new approaches to using and analyzing metadata. The same is true with AI — metadata is the key to ensuring AI-ready data.” — Gartner, January 2025. Gartner, How to Evaluate AI Data Readiness, Mark Beyer, Ehtisham Zaidi, Roxane Edjlali, 31 January 2025. GARTNER is a registered trademark and service mark of Gartner, Inc. and/or its affiliates in the U.S. and internationally and is used herein with permission. All rights reserved.
Dremio’s contributions to Apache Polaris align with its core focus on driving interoperability and scalability across data ecosystems. With Polaris’ growing momentum, key upcoming features like unstructured data support and catalog federation will further establish it as the go-to solution for organizations seeking to unify and manage their data across an increasingly fragmented landscape. To explore more about Polaris, visit the GitHub repo and the Apache Polaris (incubating) website.
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