Clearing Up Misconceptions about Data Insertion Speed in Milvus

Misconceptions about data insertion speed in Milvus may arise due to users overlooking the detailed process steps involved. When using libraries like LangChain or LlamaIndex, these platforms convert unstructured data into vectors and then insert them into Milvus Lite. The abstraction of this complex process can create an illusion that the data insertion process takes a long time. However, the actual time-consuming step is generating embeddings from unstructured data, which is computationally intensive. In comparison, the average Milvus vector database insert time is only about a tenth of a second. Thus, around 97% of the "Milvus insert" time observed in LangChain or LlamaIndex is spent on embedding generation, while about 3% is spent on the actual database insertion step.