Snowflake’s announcement that it will acquire Select Star, a San Francisco–based metadata platform, is a statement about what matters next in enterprise data. After years of powering data at scale, Snowflake is now moving toward what makes that data trustworthy and usable.

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The race for context

Over the past few years, Snowflake has been assembling this capability piece by piece. It brought in Datometry to help enterprises migrate legacy databases seamlessly, Crunchy Data to run PostgreSQL workloads natively inside its Artificial Intelligence (AI) Data Cloud, and Neeva to add advanced search and retrieval AI. With Select Star bringing unified metadata and context, Snowflake’s direction becomes clearer, a pipeline that moves data, organizes it, understands it, and equips AI to interpret it reliably.

This pattern is not unique to Snowflake. Across the ecosystem, platforms are absorbing metadata capabilities directly into their cores. Coalesce acquired CastorDoc to embed cataloging and metadata within transformation workflows, ServiceNow integrated data.world’s catalog to anchor metadata in operational processes, while Salesforce acquired Informatica to bring data management and lineage closer to its customer platform. What used to be a separate layer of metadata and governance is now becoming part of the platforms where data already lives.

As the ecosystem shifts toward AI- and agent-driven applications, the next competitive frontier is enterprise context. The platforms that can unify that context and make it usable across tools and agents will be the ones that differentiate. Snowflake’s Select Star acquisition positions it squarely in that race.

What will shape the next phase

As more platforms embed their own metadata layers, the question of openness will grow louder. If context cannot move across clouds, enterprises will end up with smarter platforms but a more fragmented ecosystem. This is why emerging open standards such as the Model Context Protocol (MCP) and OpenLineage are becoming important. Snowflake’s participation in the Open Semantic Interchange (OSI) initiative reinforces this direction, reflecting an industry-wide push toward shared semantic standards that keep context consistent and portable across tools and platforms.

This evolution also reaches into governance. As metadata becomes core to how platforms operate, governance will increasingly involve ensuring that AI interprets data consistently and that those interpretations remain traceable and trustworthy across systems.

What this means for enterprises

In the short term, architectures will simplify. Lineage, discovery, and context that once required separate tools will begin appearing natively inside Horizon, reducing the number of moving parts for teams working in Snowflake.

Over time, this consolidation raises strategic questions. As Snowflake’s environment becomes more capable, enterprises will need to consider how much of their governance approach they want shaped by a single platform, and how much platform flexibility they want to retain across the rest of their stack. It also brings into focus how teams choose their context tools. Enterprises have traditionally paired each workload with the catalog native to its platform. Whether Snowflake’s broader metadata reach changes that pattern or continues to sit alongside other catalog layers in the stack remains to be seen.

What this means for catalog providers

This acquisition also brings a change for the catalog platforms that integrate with Snowflake today. As more metadata and lineage become native inside Horizon, these providers will need to reassess where they add value for Snowflake customers and how they position themselves alongside a stronger native experience. Their role will depend on two things: how Snowflake integrates Select Star into Horizon, and how it maintains its broader catalog partnerships. The rest will be shaped by enterprise needs especially for visibility across the systems and workflows that sit outside Snowflake.

A related question is the future of “catalog of catalogs” tools designed to unify metadata across fragmented estates. Their path becomes less certain as major platforms expand their own cross-system cataloging capabilities.

The takeaway

Snowflake’s Select Star acquisition captures a broader turning point. In a market where every platform promises AI readiness, context has become the new currency of trust.

For enterprises, it is a reminder that the next edge will not come from collecting more data, but from finally understanding what they already have, and letting that understanding drive how AI learns, decides, and acts.

If you enjoyed this blog, check out, Snowflake Acquires Crunchy Data to Strengthen Enterprise AI Ambitions – Everest Group Research Portal, which delves deeper into another topic relating to Snowflake.

To take the conversation forward, please contact Mansi Gupta ([email protected]) and Anju Kattakathu ([email protected]).