Vector databases have gained attention for efficiently storing and managing high-dimensional data, crucial for AI and generative AI applications. Retrieval-augmented generation (RAG) integrates up-to-date information from external knowledge bases using specialized vector databases. However, limitations of vector databases, such as complex query support and data-type restrictions, have become apparent. Integrating vector search into SQL databases offers a compelling alternative, balancing efficiency and familiarity. MyScaleDB, an open-source SQL vector database, combines traditional SQL strengths with vector capabilities, outperforming specialized vector databases in speed and cost-effectiveness. While specialized vector databases excel in precision and speed, a hybrid approach with integrated vector search offers a more versatile solution. MyScaleDB’s ability to manage both structured and vector data makes it a powerful and flexible option for modern AI applications, preparing data infrastructure for future needs.
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Source link: https://medium.com/@myscale/dont-build-your-future-on-specialized-vector-databases-89f912762eb9?source=rss——ai-5
Avoid relying on specialized vector databases for future success. #DataScience
