CyborgDB partners with Redpanda to provide encrypted vector storage for enterprise AI applications. Traditional vector databases store embeddings in plaintext, creating security risks for sensitive data. CyborgDB encrypts vectors before storage and enables semantic search on encrypted data using cryptographic techniques like SHA3 hashing and AES-256 encryption. The integration allows organizations to build real-time AI pipelines for fraud detection, RAG applications, and semantic search while maintaining compliance in regulated industries. The article provides Docker setup instructions, configuration examples, and production deployment guidance using Docker Compose.
Table of contents
The technologies #How to add CyborgDB to your pipeline #Performance and security considerations #Production deployment with Docker Compose #Build secure pipelines with CyborgDB in Redpanda Connect #1 Impression