Starburst Enhances Platform to Accelerate and Streamline Data Consumption

Starburst, the analytics anywhere company, is unveiling the latest updates to its platform targeted toward increasing performance speeds while simultaneously making data more easily consumable, accessible, and discoverable.

Inspired by the complex workloads and its disparities among organizational data teams, Starburst “wants to bridge the gap between data analysts and data teams, where they are working on a similar platform and can create and find new data sets for business use cases—and data analysts can find all the data across all of the sources, and understand how data is being used in the organization,” said Vishal Singh, head of data products at Starburst.

Starburst’s launch of data product building in Starburst Enterprise has shaped the foundation for the enterprise’s new search and discovery function within Starburst Galaxy, allowing users to preview data products in a search and discover automated data catalog.

Users can discover a multitude of data across sources, including metadata from roles, user queries, and a variety of user behaviors, easing the workloads of data analysts and data scientists alike.

“Our mission has been, ‘how can we actually shorten the time-to-insight to drive business value?’,” said Singh. “We want to empower the data analyst in a way that they can understand the business context behind their tables, actually creating the outcome, sharing with the organization, and collaborating in the outcome to drive more and more consumption with context.”

In connection with accessibility and consumability, Starburst is continuing to invest in the Python ecosystem, encouraging data scientists to use familiar tools in accessing Starburst Enterprise and Starburst Galaxy. Developed in response to user requests for migration of PySpark workloads to Starburst and Trino, Starburst enables this capability to improve performance without tedious code rewriting.

“With the new Python ecosystem coming in, you can use the code which you already have in your workload, change the endpoint to Starburst, and keep using existing code that has already been developed to do the transformation to do a more ELT kind of workload,” said Singh. 

The announcement also leans on Starburst’s recent launch of Fault-Tolerant Execution, which ensures “that queries never fail, and it always keeps on retrying,” explained Singh.

Combined with Starburst’s Python ecosystem investments, the platform empowers data engineers and scientists to produce more accurate, agile models on more data with higher long-running query success rates, according to the company.

Starburst is additionally introducing Warp Speed, a smart indexing and caching solution built to increase query speed by 7x, while dynamically and autonomously updating cache based on usage pattern analytics.

Warp Speed optimizes data lake performance by alleviating manual labor in deciding what data in the data lake should be optimized and cached. It can further streamline data federation within multi-cloud deployment and data sharing scenarios by removing manual joins of different systems.

“Warp Speed provides smart indexing and caching where it indexes the data behind the scenes, chooses where to store it, and ultimately—based on your workload patterns—chooses what data to put into the cache,” said Ali Huselid, SVP of product at Starburst. “It’s about really optimizing the performance for those queries that are repeatable and heavily accessed via your users, typically within a dashboard, but also other types of analytical workloads that are highly repeated.”

Warp Speed is available for private preview in Starburst Galaxy and will be generally available in Starburst Enterprise by the end of February.

“Ultimately, we want to enable users to actually do the work before they even think about writing their query or consider having to move their data,” remarked Huselid. “They can do all of that upfront discovery and exploratory work before they make those bigger decisions which often result in a lot of work for moving the data or transforming the data. We save them a lot of time and make their lives a lot easier because they can make those decisions more smartly.”

To learn more about Starburst’s latest platform enhancements, please visit