Most vector database discussions happen at small scale. A few thousand documents. A few hundred users. A handful of retrieval requests. Everything feels fast. Search results look relevant. Latency stays low. Infrastructure costs appear reasonable. Then the system keeps growing. More integrations arrive. More documents get ingested. More teams start using the platform. And suddenly the vector database that felt effortless six months ago becomes one of the most important infrastructure components in the entire system. That is where the interesting problems begin. Growth Changes Everything At small scale, almost every retrieval strategy looks successful. The dataset is limited. The information is relatively clean. Relevance remains easy to maintain. Large-scale enterprise environments are completely different. Now you are dealing with: emails tickets CRM records meeting transcripts internal documentation knowledge bases shared drives historical archives The challenge is no longer storing embeddings.…