Snowflake and Databricks Want to Own Your Semantic Layer. Here's the Problem.

Snowflake and Databricks have both built semantic layers directly into their platforms. They're telling enterprise data teams the same thing: "Don't worry — we've got this. It's built in." But here's what they're not telling you. A semantic layer that lives inside your warehouse is only as universal as that warehouse. The moment your data landscape extends beyond one platform — and most enterprise data landscapes do — your single source of truth is already fragmented. In this video I break down exactly what Snowflake Semantic Views and Databricks Metric Views actually deliver, where they genuinely shine, and where they hit a wall that most organizations don't discover until they're already locked in. What we cover: ✅ The warehouse-native bet — why Snowflake and Databricks made it and why it makes sense on the surface ✅ Snowflake Semantic Views — precise capabilities and real limitations including the 50–100 column constraint and replication gap ✅ Databricks Metric Views — what Unity Catalog delivers and where the join limitations and platform lock-in hurt ✅ The core problem — why "built-in" doesn't mean "universal" ✅ Where Strategy Mosaic fits — and why sitting above the platforms changes everything Tools covered: 🔹 Snowflake Semantic Views (GA August 2025) 🔹 Databricks Unity Catalog Metric Views (GA late 2025) 🔹 Strategy Mosaic — Universal Intelligence Layer Timestamps: 00:00 — Introduction 02:48 — Snowflake Semantic Views: what it is and where it hits the wall 06:54 — Databricks Metric Views: what it is and where it hits the wall 10:00 — Your Semantic Layer SHOULD NOT be a Feature Inside a Platform 12:32 — Who SHOULD OWN Your Semantic Layer 16:39 — The Final and Honest Framing 🎬 Watch the full Semantic Layer Series: 🔗 dbt vs Cube vs AtScale vs Strategy Mosaic — The Complete Comparison Nobody Did →    • dbt vs Cube vs AtScale vs Strategy Mosaic:...   🔗 Modeling Data 10x Faster With AI →    • Modeling Data 10x Faster With AI - Strateg...   🔗 Connecting to Multiple Data Sources →    • Connecting to Multiple Data Sources - Stra...   🔗 Seamless Integration with Power BI →    • Seamless Integration with Power BI - Strat...   🔗 Seamless Integration with Tableau →    • Seamless Integration with Tableau - Strate...   🔗 Seamless Integration with Qlik →    • Seamless Integration with Qlik - Strategy ...   🔗 Seamless Integration with Microsoft Excel and Google Sheets →    • Seamless Integration with Microsoft Excel ...   Resources mentioned: 🔗 Strategy Mosaic: https://www.strategy.com/software 🔗 Snowflake Semantic Views: https://docs.snowflake.com/en/user-gu... 🔗 Databricks Metric Views: https://docs.databricks.com/aws/en/me... If this video was useful: 👍 Like and Subscribe — it helps other data professionals find this comparison 💬 Comment — are you running Snowflake, Databricks, or both? I read every reply. #semanticlayer #snowflakesemanticviews #databricks #unitycatalog #strategymosaic #snowflake #semanticlayercomparison #universalsemanticlayer #moderndatastack #dataengineering #businessintelligence #powerbi #tableau #datagovernance #analyticsengineering #metricviews #snowflakevsdatabricks #AIsemanticlayer #strategysoftware #microstrategy ━━━━━━━━━━━━━━━━━ ⚠️ DISCLAIMER The Strategist Corner is an independent channel created for educational purposes. Views are my own and not affiliated with Strategy Software. ━━━━━━━━━━━━━━━━━