Technology

Snowflake optimization startup Bluesky launches with $8.8M in funding

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Intelligent workload optimization and cost governance startup Bluesky today launched its first product and announced that it has raised $8.8 million in a seed round led by Greylock Partners to expand its offerings for Snowflake Inc. users and to span other cloud-based data systems.

The company was founded by Chief Executive Officer Mingsheng Hong and Chief Technology Officer and Zheng Shao, two engineers who had previously worked at Google LLC and Uber Technologies Inc. Bluesky’s first product provides visibility into Snowflake workload usage and costs. The service provides actionable insights and workload-specific recommendations for maximum optimization.

Bluesky argues that though modern cloud-based data systems like Snowflake have helped data teams find insights with novel techniques, existing tools make managing data at scale a challenge. Manual tuning is complex and time-consuming, while homegrown tools divert resources and attention from data teams busy keeping up with the scale and pace of the business they serve. This is where Bluesky steps in.

The company claims its product goes beyond mere cost visibility to provide deep insights into how data is used and the wider implications. Bluesky actionable insights are driven by intelligent automation that understands the data-specific challenge of workload optimization and cost governance.

Bluesky’s service analyzes query workloads to detect similar groupings, using a technology it calls “query patterns.” By intelligently watching for similar query patterns, the service can detect complex situations that simplistic visibility tools miss, suggesting high-impact tuning options for valuable workloads and increasing efficiency. It does that while looking for clear savings hiding inside the noise of regular operations, such as long-running queries that repeatedly fail without providing any value.

For tuning data layouts and warehouse settings at scale, Bluesky’s smart workload analysis looks at the impact of warehouse idle time, instance startup time, cache warmup duration and other parameters to provide recommendations specific to each organization. Data teams can use the service to skip manual trial-and-error processes of tuning and instead use Bluesky’s automation to quickly find optimal data layouts and warehouse settings, letting them focus on generating business value from data.

“The dual trends of increasing enterprise cloud consumption and vast data scale provide a huge opportunity for Bluesky,” said Jerry Chen, a partner at Greylock Partners. “Enterprises gain enormous value from data clouds already, but the market is still in its infancy. As enterprises expand and mature their use of data clouds, they will increasingly need products like Bluesky to assist their data teams to manage complexity and scale.”

Although Bluesky is only launching its first product into general availability today, the company already has a sizable client base. Notable customers include Coinbase Inc., Certik, Nextbite Brands LLC, Overlay, Houseware and Mux.

Image: Bluesky

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