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performance-features/managed-database/README.md

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## Overview of Deep Lake's Managed Tensor Database
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Deep Lake offers a serverless Managed Tensor Database to eliminates the complexity of self-hosting and substantially lowers costs. Currently, it only supports dataset queries, including vector search, but additional features for creating and modifying data being added in October 2023.
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Deep Lake offers a serverless Managed Tensor Database that eliminates the complexity of self-hosting and substantially lowers costs. Currently, it only supports dataset queries, including vector search, but additional features for creating and modifying data being added in December 2023.
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<figure><img src="../../.gitbook/assets/Deep_Lake_Embedded_vs_Managed.png" alt=""><figcaption><p>Comparison of Deep Lake as a Managed Database vs Embedded Database</p></figcaption></figure>
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### User Interfaces
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#### LangChain and LlamaIndex
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No changes are needed from the user to use the Managed Tensor Database in LangChain or LlamaIndex, since all of the methods automatically route request to the Managed Database when needed.
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The only requirement it to specify that the Vector Store should be stored in the Managed Database by specifying `dataset_path = hub://org_id/dataset_name` and `runtime = {"tensor_db": True}` during Vector Store creation.
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To use the Managed Vector Database in LangChain or Llama Index, specify `dataset_path = hub://org_id/dataset_name` and `runtime = {"tensor_db": True}` during Vector Store creation.
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#### REST API
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[rest-api.md](rest-api.md)
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{% endcontent-ref %}
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### Architecture
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The Managed Tensor Database is serverless and can deployed in the user's VPC.&#x20;
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DETAILS COMING SOON
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### Further Information:
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{% content-ref url="migrating-datasets-to-the-tensor-database.md" %}

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