Annoy and ScaNN are two popular vector search tools that differ in their search methodology, data handling, scalability, performance, flexibility, integration, ease of use, cost considerations, and security features. Annoy is a lightweight library designed for fast approximate searches on large static datasets, while ScaNN is an open-source tool optimized for high-dimensional vector data in machine learning applications. Both tools have their strengths and are suitable for different use cases. When choosing between the two, consider factors such as dataset size, data dynamics, search accuracy requirements, integration with existing systems, and available computational resources.