This blog post explores effective sharding strategies for vector databases, crucial for handling large-scale, high-dimensional data. We discuss various approaches including range-based, hash-based, and dimension-based sharding, their implementations, and trade-offs. The post includes practical Python examples using FAISS and provides insights on optimizing query performance and load balancing across shards.