Snowflake Adds Declarative Infra Management

Snowflake's new DCM Projects feature allows users to manage data infrastructure declaratively, bringing software engineering practices to Snowflake object management.

Jan Sommerfeld demonstrating Snowflake DCM Projects interface for managing data objects.
Jan Sommerfeld explains how Snowflake DCM Projects enables auditable workflows for managing data objects.· Snowflake

Snowflake is rolling out DCM Projects, a new feature designed to manage Snowflake infrastructure declaratively. This aims to bring software engineering principles like version control and audibility to data object management.

The new tool allows users to define Snowflake objects, such as databases, schemas, warehouses, roles, and grants, as code. This approach enables consistent deployment across different environments and detailed tracking of changes.

Managing Data Infrastructure as Code

Traditionally, managing complex Snowflake environments at scale has required significant coordination. DCM Projects addresses this by enabling users to define their desired state using manifest and SQL definition files.

The system then computes differences, resolves dependencies, and deploys changes automatically. This mirrors practices common in software development, making data infrastructure more manageable and auditable.

This mirrors practices common in software development, making data infrastructure more manageable and auditable.

What You Can Build

DCM Projects is initially focused on several key workflows. These include defining and managing platform infrastructure, similar to how Snowflake platform infrastructure is managed. It also supports the lifecycle of data pipelines, including views, dynamic tables, and functions.

Additionally, the tool facilitates data governance by defining roles and grants declaratively. Support for ML infrastructure and Streamlit Apps is currently under development.

Snowflake DCM Projects is now available in public preview.

© 2026 StartupHub.ai. All rights reserved. You may not republish this article in full without a license. Search engines and AI research tools may crawl and summarize for reference. Bulk reproduction or model training requires a license. See our terms.
Daniel Singer

Written by

Daniel Singer

Editor, StartupHub.ai

Daniel Singer is the editor of StartupHub.ai, a technology expert and thought leader on AI and its applications across sectors, from fintech and healthcare to developer tooling and consumer software. He writes and tests the tools covered here thoroughly and regularly, and built StartupHub.ai to give founders, operators and buyers a clearer read on what they are actually being sold.