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Vector DB

A vector database is a specialized database that stores and indexes high-dimensional vectors (numerical representations of data like text, images, or audio). In AI, it enables semantic search — finding content by meaning rather than exact keyword matches. It is the backbone of RAG (Retrieval-Augmented Generation) pipelines and Knowledge DBs.

Vector DB List

The Vector DB page under Configuration > Vector DB displays all registered vector database connections. Use the Search, Type, and Status filters to find specific entries. Toggle between card view and table view using the icons in the top-right corner.

Each entry shows:

ColumnDescription
Display NameThe name of the vector DB connection. One entry can be marked as Default.
DB TypeThe vector database engine (e.g., Qdrant).
HostThe hostname or address of the vector DB instance.
PortThe port number for the connection.
StatusACTIVE or INACTIVE.
Updated atThe last modified timestamp.
ActionsEdit or delete the connection.

Add a Vector DB

  1. Click + Add Vector DB.
  2. Fill in the required fields and click Save.
FieldRequiredDescription
Vector DB TypeYesThe database engine (e.g., Qdrant).
Display NameYesA unique name for the connection.
HostYesThe server address (e.g., qdrant.aiops.svc.cluster.local).
PortYesThe connection port (e.g., 6333).
Access KeyNoAuthentication key for the vector DB instance.
DescriptionNoA brief description of the connection.
StatusNoToggle the connection Active or Inactive. Defaults to Active.
Set as defaultNoWhen enabled, new Knowledge DBs will use this vector store by default.

Edit a Vector DB

  1. Click the edit icon (pencil) on the entry you want to modify.
  2. Update the fields as needed.
  3. Click Save.

Delete a Vector DB

  1. Click the delete icon (trash) on the entry you want to remove.
  2. Type the exact display name to confirm.
  3. Click Delete.