The Dremio Blog

Modernizing Hadoop infrastructure is essential in today's data-driven landscape. Learn how to boost performance through proven Hadoop modernization strategies.

The top 5 trends in data engineering are explored in this article

Apache Iceberg has a wide Python footprint to allow you to do the work you need to do. Whether you use pySpark, ODBC/Arrow to send SQL to engines like Dremio or use pyIceberg to do local scans of your table with DuckDB, Iceberg has a lot to offer data practitioners who love writing Python.

Storage, compute, and regulatory costs can really add up when it comes to working with and managing your data. In traditional proprietary data warehouses, you must store your data in proprietary formats, organized in proprietary catalogs, to be queried with a proprietary engine. The result is vendor lock-in which over time, allows vendors to price […]

Apache Iceberg, with its ever-expanding features, ecosystem, and support, is quickly becoming the standard format data lakehouse table. When adopting Apache Iceberg there are several paths of migration no matter where your data architecture currently resides.

This article explores how you can use Dremio Cloud to easily convert CSV files into an Iceberg table, allowing you to have more performant queries, run DML transactions, and time-travel your dataset directly from your data lakehouse storage.

The data lakehouse has emerged as the next generation of data architecture, combining the best features and capabilities of data warehouses and data lakes into a single unified platform.  For years, organizations have been using data lakes and data warehouses in a two-tiered architecture; they need the data lake’s flexibility and scalability in order to […]

Domo, the cloud-based business intelligence (BI) and data analytics platform, recently announced the launch of a new native connector for Dremio. This new connector to Dremio extends the data lakehouse to Domo, enabling Domo users to easily analyze large amounts of data from a variety of new sources without having to move or copy data. […]

This blog introduces the newly added branching and tagging capabilities for Iceberg tables using Spark.

Everyone recognizes that data platforms are critical for making data-driven decisions in all functions of an enterprise. A flaw in the foundation of your data platform can have significant cost and lost revenue implications.

That’s a wrap on Subsurface LIVE 2023! I personally had a blast meeting and hanging out with folks in person in San Francisco, and I know my colleagues did as well in New York and London - not to forget the folks attending virtually (all 7,096 of you!). We were glad to see so many […]

This blog presents the benefit of the ROLLBACK table feature in Apache Iceberg that can help with data incidents.

Blog that shows how to utilize Iceberg APIs to do pruning for Dremio's reflections (a query acceleration technology)

Learn how to connect Apache Iceberg tables to view in Tableau using Dremio.

Learn how to create Apache Iceberg tables with Nessie catalog and use Nessie to create and merge branches.