Without a way to store data persistently, it gets lost after a while. Applications typically only hold data as long as they’re running. Once they stop, the data’s lost. Sometimes, data in the application’s memory can even be lost due to the underlying framework or operating system actions.
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Why Databases Matter for RAGs
Databases provide effective memory storage for your app. They remember not only the retrieved data but also context from previous prompts.
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Vector Databases and RAG
For LLMs, vector databases are the ideal storage solution. Vector embeddings are numerical representations designed to capture the semantic meanings of data — most commonly text, but also other data types like emojis and media.
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This content was released on Nov 12 2024. The official support period is 6-months
from this date.
Understand the different types of embedding strategies and the importance of using vector databases in a RAG application.
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