Oracle Database Vector Store: Insert
AI-generatedOverview
This node inserts vector embeddings and their associated documents into an Oracle Database vector store table. It is designed to work with AI-generated documents and embeddings, enabling efficient storage and retrieval of vectorized data within an Oracle database environment.
Common scenarios include:
- Storing processed AI documents and their embeddings for semantic search or similarity queries.
- Managing vector data in Oracle databases for applications like recommendation systems, natural language processing, or knowledge management.
- Clearing existing data in a vector store table before inserting new vectors to maintain up-to-date datasets.
For example, after generating document embeddings from text data, this node can insert those embeddings into a specified Oracle table, optionally clearing the table first to replace old data.
Properties
| Name | Meaning |
|---|---|
| Table Name | The name of the Oracle database table where the vector embeddings and documents will be inserted. This is required. |
| Clear Table | Whether to clear (delete all rows from) the specified table before inserting new data. Options: true (clear table), false (append data). Default is false. |
Output
The node outputs an array of JSON objects representing the serialized documents that were inserted into the Oracle vector store. Each output item corresponds to a processed document enriched with its embedding data, ready for further use or inspection downstream in the workflow.
No binary data output is produced by this node.
Dependencies
- Requires the Oracle Database Node.js driver (
oracledbpackage) to be installed in the n8n environment (npm install oracledb). - Requires an Oracle Database connection credential configured in n8n, including host, port, user, password, and service name.
- Uses a custom OracleDbVectorStore class to manage vector storage operations.
- The node dynamically loads Oracle dependencies at runtime and throws an error if they are missing.
Troubleshooting
- Missing Oracle module error: If the node throws an error about missing Oracle dependencies, ensure the
oracledbpackage is installed in your n8n environment. - Connection failures: Verify that the Oracle database credentials and network connectivity are correct. Check host, port, user, password, and service name parameters.
- Table does not exist: Ensure the specified table name exists in the Oracle database and has the appropriate schema to store vector embeddings.
- Permission issues: The database user must have sufficient privileges to connect, clear, and insert data into the target table.
- Clearing large tables: Enabling "Clear Table" on very large tables may cause performance delays; consider managing data retention policies accordingly.