Epsilla – Open-source vector database with low query latency
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…
Epsilla – Open-source vector database with low query latency launched on August 14, 2023 with 111 votes, #609 of 4,347 launches that month and more than 95% of that year's launches. The site was still online in September 2026, 3 years on.
In plain words
Epsilla is an open-source, self-hostable vector database designed for semantic similarity search with optimized low query latency. It helps applications find the most relevant content from large document pools to feed into language models with context limits. The database specializes in maintaining fast query speeds even when precision requirements exceed 95%, addressing performance degradation issues common in traditional vector indexing approaches.
written from the facts on this page · September 2026
From the sources
Epsilla is a high performance Vector Database Management System - epsilla-cloud/vectordb
In the maker’s words, at launch
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…
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