What Is a Real Vector Database?

The emergence of ChatGPT has signaled the start of a new era in artificial intelligence (AI), with vector databases becoming an essential infrastructure. Vector databases store and retrieve unstructured data such as images, audio, videos, and text through high dimensional values called embeddings. They are frequently used for similarity searches using the Approximate Nearest Neighbor (ANN) algorithm. Specialized vector databases like Milvus and Zilliz Cloud offer many user-friendly features and are a more optimal solution for unstructured data storage and retrieval compared to vector search libraries. Vector databases are becoming vital infrastructure for AI-related tech stacks, such as LLM augmentation, recommender systems, image/audio/video/text similarity searches, anomaly detection, question-answering systems, and molecular similarity searches. To choose the most suitable vector database for your project, VectorDBBench is an open-source benchmarking tool that evaluates various vector database systems regarding QPS, latency, capacity, and other metrics.

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