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Skeg

The memory-efficient vector DB with high recall.

Developer Tools
Artificial Intelligence
Database
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Hunted byDaniele ScarattiDaniele Scaratti

Skeg is a multi-tenant vector database built for extreme RAM efficiency: pack far more vectors per GB without trading away recall. Purpose-built for high-density, many-tenant deployments where memory is the bottleneck, not an afterthought. Open source, written in Rust.

Top comment

Hey everyone! 👋 Excited to finally launch Skeg on Product Hunt. We built Skeg because we were frustrated with the usual trade-offs in vector databases: either great recall but huge RAM usage, or low memory but poor performance under real load. Skeg is a disk-first vector database that focuses on memory efficiency while maintaining high recall. It works especially well in multi-tenant SaaS environments, RAG systems running alongside LLMs, and ARM-powered machines. Would love to hear your thoughts: What vector search tools are you currently using? What’s your biggest pain point with vector databases today? Happy to answer any questions! Repo: https://github.com/skegdb/skeg Thank you for checking it out!

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About Skeg on Product Hunt

The memory-efficient vector DB with high recall.

Skeg was submitted on Product Hunt and earned 6 upvotes and 1 comments, placing #41 on the daily leaderboard. Skeg is a multi-tenant vector database built for extreme RAM efficiency: pack far more vectors per GB without trading away recall. Purpose-built for high-density, many-tenant deployments where memory is the bottleneck, not an afterthought. Open source, written in Rust.

Skeg was featured in Developer Tools (517.5k followers), Artificial Intelligence (475.9k followers) and Database (2.2k followers) on Product Hunt. Together, these topics include over 194.1k products, making this a competitive space to launch in.

Who hunted Skeg?

Skeg was hunted by Daniele Scaratti. A “hunter” on Product Hunt is the community member who submits a product to the platform — uploading the images, the link, and tagging the makers behind it. Hunters typically write the first comment explaining why a product is worth attention, and their followers are notified the moment they post. Around 79% of featured launches on Product Hunt are self-hunted by their makers, but a well-known hunter still acts as a signal of quality to the rest of the community. See the full all-time top hunters leaderboard to discover who is shaping the Product Hunt ecosystem.

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