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For AI workloads, core evaluation criteria include compute-storage separation, open standards compatibility, scale-to-zero, connection architecture, AI-native capabilities and integrated governance. This article is a practical buyer's guide for developers, architects and data leaders evaluating serverless databases for AI applications, including a vendor checklist. For teams building AI applications today, serverless databases are the new baseline. AI teams need a database that scales instantly with demand, idles at near-zero cost and stays close to enterprise data. Otherwise, they risk paying for unused infrastructure, creating governance, security and compliance challenges and spending valuable time on database management. What is a serverless database? 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