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Oracle AI Database is built for AI workloads where you query data by meaning (semantics), not just keywords. It combines semantic search over unstructured content with relational filtering over business data in one system—so you can build AI retrieval workflows (like RAG) without introducing a separate vector database and fragmenting data across multiple platforms.

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Why it matters

  • One system for AI + business data: vectors and operational data live together.
  • Less fragmentation: fewer moving parts than a separate vector store.
  • Database-grade guarantees: apply security, transactions, scale, and availability to the same AI workload.

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Prerequisites

Install langchain-oracledb. The python-oracledb driver will be installed automatically as a dependency.

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Document loaders

Please check the usage example.

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Text splitter

Please check the usage example.

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Embeddings

Please check the usage example.

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Summary

Please check the usage example.

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Vector store

Please check the usage example.

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End to end demo

Please check the Oracle AI Vector Search End-to-End Demo Guide.

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Additional resources

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