Milvus is a high-performance, cloud-native vector database built for scalable vector ANN search
An Approximate Nearest Neighbors library in Rust, based on random projections and LMDB and optimized for memory usage 💥
A low-latency, billion-scale, and updatable graph-based vector store on SSD.
Production-ready KV-backed HNSW implementation in Rust using LMDB
🧬🔍 Vecgo is a pure Go, embeddable, hybrid vector database designed for high-performance production workloads. It combines commit-oriented durability with HNSW + DiskANN indexing for best-in-class performance.
Türkçe SQL Server 2025 başucu kitabı — kod örnekleri, errata, topluluk Q&A · CC BY-NC-SA 4.0 + MIT
Open-source community study guide for Microsoft DP-800: Developing AI-Enabled Database Solutions. Aligned to the March 2026 official blueprint. Covers SQL Server 2025, Azure SQL, Microsoft Fabric, vector search, RAG, MCP, and more.
A modular framework for evaluating disk-based vector search, enabling controlled ablations and end-to-end comparisons across diverse storage environments, concurrency regimes, and query distributions.
DiskANN in Pure Rust — Built for Large-Scale Approximate Nearest Neighbor Search.
A native Rust implementation of DiskANN (Disk-based Approximate Nearest Neighbor search) 🦀
Jigen DB is vector database written from scratch in c#
Pure Rust Port of DiskANN
Julia Implementation of Low Memory Disk ANN (LM-DiskANN)
DiskANN vs HNSW: a measured vector-index benchmark at 3.38M and 10K scale (recall/QPS/memory, concurrency, reproducible harness)
VIC-style tiered retrieval demo with native KIOXIA AiSAQ for low-DRAM, storage-aware semantic search.
Retrieval-focused database for local text, vector, and hybrid search — with a Python SDK, CLI, and retrieval SQL.
SQL Server 2025 native vector search + AI_GENERATE_EMBEDDINGS over StackOverflow, exposed to AI agents via Data API builder's built-in MCP server — no separate vector DB, embedding service, or API tier.
Security-first, memory-frugal vector database in Rust with a retro terminal cockpit.
Python source code files to visualize DiskANNs Latency Throughput graph