The Dremio Blog

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.

Answers to many of the most common questions about Apache Iceberg.

This tutorial provides a step-by-step guide to migrate an Apache Superset dashboard built on a cloud data warehouse to an open lakehouse.

Learn how to take advantage of Dremio Arctic’s capability to commit transactions to multiple tables simultaneously.

This tutorial shows how Dremio Arctic supports experimentation and reproducibility of machine learning models in the data lakehouse using Apache Iceberg, Spark & Dremio.

This tutorial presents a notebook guide to quickly get started with Apache Iceberg & Nessie using PySpark

Dremio now offers the capability to both query and manipulate data stored in Apache Iceberg table format. In this blog, we’ll show how Dremio can be used to create and amend Iceberg datasets. Then we’ll take a look at how we can step back in time in order to examine the state of the table at earlier points in time.

In this blog, learn how Dremio helps end users analyze massive datasets in their semantic layer without sacrificing speed or ease of use.

Why does adopting a data lakehouse table format like Apache Iceberg matter and how it solves issues like data drift, costs, and more.

A semantic layer is a business representation of corporate data for your end users.