Azure SQL Hyperscale is presented as a way to avoid 'polyglot tax' — the operational, cost, and cognitive overhead of managing multiple specialized databases (vector, graph, document, analytics). Microsoft SQL's core engine now natively supports JSON with path-level indexing, graph queries, vector types with DiskANN-based indexes, and columnar storage for analytics, all within a single ACID-compliant system. Hyperscale adds cloud-native scalability up to 128 TB, snapshot-based backups, named replicas with isolated buffer pools for separating OLTP and analytical workloads, serverless scaling, and an MCP server via Data API Builder for agentic access. The talk argues this consolidation reduces latency, security surface area, operational complexity, and cost compared to running separate specialized databases.