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Vector databases (beyond the hype)

Practical AI: Machine Learning, Data Science, LLM

The challenge of optimizing existing databases for vector solutions

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  • Existing databases have their own tech debt and architectural decisions that make it challenging to implement vector solutions from day one.
  • Incumbent vendors may take a significant amount of time to optimize their offerings to perform as well as purpose-built vendors.
  • Purpose-built offerings may have features that are not available in existing solutions.
  • Young solutions like Me, G-vector and Elasticsearch's vector offering may still be lacking in capabilities compared to established databases.

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