The Dremio Blog

This is the second article in the series of building a Modern Data Platform.

Data lakes can be agile, low-cost ways for companies to store their data. By incorporating key elements into their design, you can build the right tools to keep it from becoming a data swamp.

If you Google 'modern data platform' you will get a lot of advertisement. Let’s try to agree on what modern data platform is.

ODBC and JDBC were invented 27 years ago, Apache arrow arrived to bring the best-in-class performance in the big data world.

Described by Microsoft as a “no-compromise data lake”, ADLS Gen 2 extends the capabilities of Azure Blob Storage and is optimized for large scale analytics workloads.

How Hotmart uses Dremio to gain insights from data, faster.

Learn how to add User Defined Functions to Gandiva.

Exploring performance improvements for SQL processing in Dremio based on Gandiva Initiative for Apache Arrow.

In-depth technical description of Dremio's Gandiva Initiative for Apache Arrow.

Apache Arrow was announced as a top level Apache project on Feb 17, 2016. We wanted to give some context regarding the inception of the project, as well as interesting developments as the project has evolved.

Behind the scenes, invisible to end users, a relational cache comprising data materializations, also known as Data Reflections™, enables Dremio to accelerate queries from users and tools.

Learn how I built the winter olympics data analysis story using Dremio.

Learn how we built a twitter sentiment analysis using Dremio, Tableau, and more.

Technical performance review of enhancements to Java vectors in Apache Arrow 0.8.0

Our CEO reflects on two years of stealth and exiting Dremio from stealth.