Starburst, the open data lakehouse company, announced at Data Universe its fully managed Icehouse implementation on Starburst’s multi-cloud data lakehouse service, Galaxy. With the Galaxy Icehouse, customers can benefit from the scalability, performance, and cost-effectiveness of a combined Trino and Iceberg architecture (Icehouse) without the burden and cost of building and maintaining a custom solution themselves. This announcement builds on the strong momentum of Starburst Galaxy including 3x year-over-year growth in both active customers and usage volume. Starburst is setting new benchmarks in the industry, proven by the rapid adoption of its Galaxy platform, addressing customers’ need for an open data lakehouse architecture. Customers can sign up for early access to Galaxy Icehouse here starting today.
Organizations are increasingly turning to an open data lakehouse architecture to power interactive applications and run their business. As seen in the Icehouse Manifesto, the open-source Trino query engine combined with the Apache Iceberg table format provides powerful scalability, cost-effectiveness, and query performance without the risk of vendor lock-in. The Icehouse architecture underpins some of the most sophisticated lakehouses on the planet, including those at Netflix, Apple, Shopify, and Stripe. Effectively operationalizing an Icehouse requires handling data ingestion, data governance, Iceberg data management, and capacity management at scale, especially in multi-cloud environments. Unfortunately, most organizations don’t have the time or expert resources required to fully implement and benefit from the Icehouse architecture.
Today, Starburst announced its fully managed implementation of an Icehouse in Starburst Galaxy. Starburst’s Icehouse builds on the proven Trino SQL analytics, governance, and auto-scaling capabilities in Starburst Galaxy, and adds new support for near real-time data ingestion at petabyte-scale into managed Iceberg tables. However, ingesting data at scale is not enough—the data isn’t useful to an organization until it meets its correctness and performance requirements, delivering end-user value in the form of live apps and dashboards. With Starburst’s Icehouse, customers’ data and development teams can use easy-to-use Structured Query Language (SQL) to prepare and optimize their data and make it available for production use in near real-time. Further, building on the auto-tuning capabilities in Starburst Warp Speed, Starburst’s Icehouse automatically uses the optimized data to improve query performance, enabling interactive use cases without requiring costly expert tuning and code changes.
“Adding a fully managed Icehouse implementation to Starburst Galaxy marks a significant milestone in our journey to provide the most advanced and user-friendly open data analytics platform available,” said Justin Borgman, co-founder and CEO of Starburst. “This enhancement, combined with our suite of innovative features, empowers customers to navigate the complexities of data and analytics with greater ease, efficiency, and accuracy.”
Starburst Galaxy is making significant strides across industries, demonstrating its impact on data management and analytics.
- “The move to Starburst and Iceberg has resulted in a 12x reduction in compute costs versus our previous data warehouse. This efficiency allows us to focus our attention on using analytics for revenue-generating opportunities,” said Peter Lim, Sr. Data Engineer, Yello.
- “Starburst Galaxy has been a game-changer for our team, significantly enhancing our data pipeline performance. Our analysts are thrilled with the faster response times, while our stakeholders appreciate the expedited updates to their dashboards. The combination of Starburst Galaxy and Apache Iceberg offers exceptional value, delivering far more for the same investment. It’s a clear win for efficiency and productivity in our data-driven environment,” said Johni Michels, Data Team Lead, Kovi.
- BestSecret transitioned from a monolithic system to a decentralized Starburst and Iceberg setup, enabling direct analytics on data, thus bypassing traditional data warehousing steps and achieving notable cost reductions, as described by Lutz Künneke, Director of Engineering at BestSecret.
SOURCE: PRNewsWire