This post explores the synergy between InfluxDB and Milvus for handling time series data and performing similarity searches. It covers generating dummy traffic data, writing and querying data from InfluxDB, normalizing and vectorizing time series data, and inserting it into Milvus. It also discusses creating a collection and performing a similarity search in Milvus.
Table of contents
RequirementsWhat is a vector database?A TSDB and vector database scenarioBeginning stepsWriting and querying Pandas DataFrames from InfluxDBWindowing, normalizing, and vectorizing time series dataCreating a collection and inserting the entity to MilvusPerforming a similarity searchFinal thoughts2 Impressions