Agentic AI systems can work with both vector databases and data warehouses, depending on the application:

• Vector databases are used when AI models need to perform similarity searches or work with high-dimensional data, such as embeddings from machine learning models
• Data warehouses (e.g., Snowflake) are typically used for structured data and analytics, where AI systems query historical data or aggregated information

Snowplow integrates with both types of databases, allowing businesses to feed AI systems with the necessary data for real-time decision-making. Snowplow Signals bridges this gap by providing a unified system that can compute attributes from both warehouse data and real-time streams, making them available through APIs regardless of the underlying storage architecture.