VectorDBZ

What it does

VectorDBZ - Professional desktop application for managing and analyzing vector databases. Connect to Qdrant, Weaviate, Milvus, ChromaDB, Pinecone, pgvector (PostgreSQL), and more. Enterprise-grade features for vector analysis, visualization, and performance optimization.

• VA
  VectorDBZ, a desktop GUI for vector databasesJan 2026 · github.com · ▲13

  Hi HN, I built VectorDBZ, a cross-platform desktop app for exploring and analyzing vector databases like Qdrant, Weaviate, Milvus, and ChromaDB. It lets you browse collections, inspect vectors and metadata, run similarity searches, and visualize embeddings without writing custom scripts. GitHub (downloads and issues): https://github.com/vectordbz/vectordbz Feedback welcome. If it’s useful, starring the repo helps keep me motivated. Thanks.

• PA
  Postgres as a VectorDB GUI2024 · github.com · ▲162
• HO
  HelixDB – Open-source vector-graph database for AI applications (Rust)2025 · github.com · ▲237

  Hey HN, we want to share HelixDB (https://github.com/HelixDB/helix-db/), a project a college friend and I are working on. It’s a new database that natively intertwines graph and vector types, without sacrificing performance. It’s written in Rust and our initial focus is on supporting RAG. Here’s a video runthrough: https://screen.studio/share/szgQu3yq. Why a hybrid? Vector databases are useful for similarity queries, while graph databases are useful for relationship queries. Each stores data in a way that’s best for its main type of query (e.g.…

• VY
  VectorVFS, your filesystem as a vector database2025 · vectorvfs.readthedocs.io · ▲279
• EO
  Epsilla – Open-source vector database with low query latency2023 · github.com · ▲111

  Hey HN! We are building Epsilla (https://github.com/epsilla-cloud/vectordb), an open-source, self-hostable vector database for semantic similarity search that specializes in low query latency. When do we need a vector database? For example, GPT-3.5 has a 16k context window limit. If we want to let it answer a question about a 300 page book, we cannot put the whole book content into the context. We have to choose the sections of the book that are most relevant to the question. Vector database is specialized at ranking and picking the most relevant content from a large pool…

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