Desktop Tool for Vector Database Inspection and Debugging
Published:Jan 1, 2026 16:02
•1 min read
•r/MachineLearning
Analysis
This article announces the creation of VectorDBZ, a desktop application designed to inspect and debug vector databases and embeddings. The tool aims to simplify the process of understanding data within vector stores, particularly for RAG and semantic search applications. It offers features like connecting to various vector database providers, browsing data, running similarity searches, generating embeddings, and visualizing them. The author is seeking feedback from the community on debugging embedding quality and desired features.
Key Takeaways
- •VectorDBZ is a desktop application for inspecting and debugging vector databases.
- •It supports multiple vector database providers (Qdrant, Weaviate, Milvus, Chroma).
- •Key features include browsing data, similarity search, embedding generation, and visualization.
- •The tool aims to speed up exploratory analysis and debugging in retrieval and RAG systems.
- •The author is seeking feedback on debugging embedding quality and desired features.
Reference
“The goal isn’t to replace programmatic workflows, but to make exploratory analysis and debugging faster when working on retrieval or RAG systems.”