Docs Connect Components Catalog Outputs cyborgdb cyborgdb Available in: Self-Managed Inserts items into a CyborgDB encrypted vector index. Introduced in version 4.66.0 Common Advanced outputs: label: "" cyborgdb: max_in_flight: 64 batching: count: 0 byte_size: 0 period: "" check: "" processors: [] # No default (optional) host: "" # No default (required) api_key: "" # No default (required) index_name: redpanda-vectors index_key: "" # No default (required) operation: upsert id: "" # No default (required) vector_mapping: "" # No default (optional) metadata_mapping: "" # No default (optional) outputs: label: "" cyborgdb: max_in_flight: 64 batching: count: 0 byte_size: 0 period: "" check: "" processors: [] # No default (optional) host: "" # No default (required) api_key: "" # No default (required) index_name: redpanda-vectors index_key: "" # No default (required) create_if_missing: false operation: upsert id: "" # No default (required) vector_mapping: "" # No default (optional) metadata_mapping: "" # No default (optional) This output allows you to write vectors to a CyborgDB encrypted index. CyborgDB provides end-to-end encrypted vector storage with automatic dimension detection and index optimization. All vector data is encrypted client-side before being sent to the server, ensuring complete data privacy. The encryption key never leaves your infrastructure. Fields api_key The API key for authenticating with the CyborgDB service. This key identifies your account and provides access to your CyborgDB indexes. Keep this key secure and avoid exposing it in logs or version control. This field contains sensitive information that usually shouldn’t be added to a configuration directly. For more information, see Secrets. Type: string batching Allows you to configure a batching policy. Type: object # Examples: batching: byte_size: 5000 count: 0 period: 1s batching: count: 10 period: 1s batching: check: this.contains("END BATCH") count: 0 period: 1m batching.byte_size An amount of bytes at which the batch should be flushed. If 0 disables size based batching. Type: int Default: 0 batching.check A Bloblang query that should return a boolean value indicating whether a message should end a batch. Type: string Default: "" # Examples: check: this.type == "end_of_transaction" batching.count A number of messages at which the batch should be flushed. If 0 disables count based batching. Type: int Default: 0 batching.period A period in which an incomplete batch should be flushed regardless of its size. Type: string Default: "" # Examples: period: 1s period: 1m period: 500ms batching.processors[] A list of processors to apply to a batch as it is flushed. This allows you to aggregate and archive the batch however you see fit. Please note that all resulting messages are flushed as a single batch, therefore splitting the batch into smaller batches using these processors is a no-op. Type: processor # Examples: processors: - archive: format: concatenate - archive: format: lines - archive: format: json_array create_if_missing Whether to create the index if it doesn’t exist. When enabled, CyborgDB automatically detects the vector dimensions from your data and optimizes the index configuration for performance. This is useful for development and testing environments. Type: bool Default: false host The host URL for the CyborgDB instance. This should include the protocol (https://) and port number if required. For example: https://api.cyborgdb.com or https://localhost:8080. Type: string # Examples: host: api.cyborg.com host: localhost:8000 id A Bloblang mapping that determines the unique identifier for each vector entry. This ID is used to update existing vectors during upsert operations or to specify which vectors to delete. If not provided, CyborgDB will generate unique IDs automatically. This field supports interpolation functions. Type: string index_key The base64-encoded encryption key for the CyborgDB index. This key must be exactly 32 bytes when decoded from base64. All vector data is encrypted client-side using this key before transmission, ensuring complete data privacy. Store this key securely as it cannot be recovered if lost. This field contains sensitive information that usually shouldn’t be added to a configuration directly. For more information, see Secrets. Type: string # Examples: index_key: your-base64-encoded-32-byte-key index_name The name of the CyborgDB index to write vectors to. If the index doesn’t exist and create_if_missing is enabled, CyborgDB will create it automatically with optimized settings based on your data. Type: string Default: redpanda-vectors max_in_flight The maximum number of messages to have in flight at a given time. Increase this to improve throughput. Type: int Default: 64 metadata_mapping An optional Bloblang mapping that extracts metadata to associate with the vector entry. The metadata can contain any JSON-serializable data that helps identify or categorize the vector. This data is stored encrypted alongside the vector. Type: string # Examples: metadata_mapping: root = @ metadata_mapping: root = metadata() metadata_mapping: root = {"summary": this.summary, "category": this.category} operation The operation to perform against the CyborgDB index. Supported operations: upsert: Insert new vectors or update existing ones (requires vector_mapping) delete: Remove vectors from the index (requires id) query: Search for similar vectors (requires vector_mapping) Type: string Default: upsert Options: upsert, delete vector_mapping A Bloblang mapping that extracts the vector from the message. The result must be an array of floating-point numbers representing the vector embeddings. This field is required for upsert and query operations. Type: string # Examples: vector_mapping: root = this.embeddings_vector vector_mapping: root = [1.2, 0.5, 0.76] Back to top × Simple online edits For simple changes, such as fixing a typo, you can edit the content directly on GitHub. Edit on GitHub Or, open an issue to let us know about something that you want us to change. Open an issue Contribution guide For extensive content updates, or if you prefer to work locally, read our contribution guide . Was this helpful? thumb_up thumb_down group Ask in the community mail Share your feedback group_add Make a contribution 🎉 Thanks for your feedback! couchbase cypher