Azure Data Lake: Powered by Starburst Galaxy

Published: December 2, 2021
Last Updated: April 6, 2023

Earlier this week, we announced the launch of Starburst Galaxy on Microsoft’s Azure cloud service. Starburst Galaxy is the new fully-managed SaaS service from Starburst that provides enterprise-ready Starburst clusters which can be deployed within minutes. With one of the lowest TTQ (Time to Query) engines on the market, means you can provide your analytical users with a self-service query platform against Azure Data Lake Storage (ADLS) and other Azure data sources without dedicating valuable resources to deploy and manage these resources.

“We’re excited to partner with Starburst to provide our customers with the power of Microsoft’s Azure cloud platform alongside Starburst Galaxy.”, said Ken Miller, General Manager, West Region Cloud, Microsoft. “The combination of our two products will help our customers add tremendous value to their data ecosystem.”

The Starburst engine powers Starburst Galaxy. It is the best-in-class MPP SQL engine originally based on open source Trino with enterprise enhancements made by Starburst. Developed out of Facebook as a replacement for Hive to query their massive data lake, Trino has quickly become the de facto data lake and lakehouse query engine over numerous different storage systems such as ADLS.

Azure’s ADLS (Azure Data Lake Storage) is a low-cost storage solution that provides a high-performance along with a high level of redundancy making it the perfect solution for a company’s default storage location. As companies migrate off Hadoop and legacy based data warehouses, they are choosing ADLS as the new home for this data which allows different “process engines” to work on this data to perform many different business functions such as analytics.

0 to Querying ADLS in < 5 min !

Starburst Galaxy can provision new clusters within minutes into any Azure region that houses your data. In the diagram below, Starburst SQL query clusters are deployed in the same region as the data eliminating egress costs and ensuring maximum performance. Creating new clusters and adding data sources takes just a few clicks and from there, querying data can be performed using the query editor provided within Galaxy or any BI or SQL tool such as Power BI, DBeaver and data science notebooks such as Jupyter.

Starburst Galaxy

Starburst Galaxy makes it very easy to query your Azure ADLS data lake with 4 easy steps:

How to setup Starburst Galaxy

If you have data in MySQL or PostgreSQL, you can query those data sources and even federate data between them if needed. For more information about these features, please see our previous blog post titled: Azure Data Mesh: Powered by Starburst.

In the demo below, we show you how easy it is to create a Galaxy account and start querying your Azure ADLS data within a few minutes:


As you can see from the demo, Galaxy provides one of the fastest TTQ (time to query) SQL query engines for Azure. Some other features provided by Galaxy are:

  • Suspend mode – Clusters can be set to go into “suspend” mode while not being used. When a cluster is in suspended mode, there are no charges being incurred. When a new query is executed against the suspended cluster, it will start up and complete the query.
  • Blue/Green deployments – Galaxy deploys new clusters behind the scenes for configuration changes and upgrades ensuring there is a seamless, uninterrupted experience for end users.
  • Query Editor – built-in, easy to use web-based query editor. No need to install extra software just to query your ADLS and other data sources

Starburst Galaxy enables querying Azure data lakes with just a few clicks. This provides self-service analytics by providing the industry leading SQL based query engine in a fully managed service.

Sign-up today to receive up to $500 in free credits. Learn more here!

Start Free with
Starburst Galaxy

Up to $500 in usage credits included

  • Query your data lake fast with Starburst's best-in-class MPP SQL query engine
  • Get up and running in less than 5 minutes
  • Easily deploy clusters in AWS, Azure and Google Cloud
For more deployment options:
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