Original Summary

Hi HN, I&#x27;m Daniel, co-founder of Seafile.<p>I&#x27;m glad to share our open-sourcing project SeaSearch, a search engine written in Go (built on ZincSearch) that we’ve been running in production for over two years for Seafile project.<p>After years of using Elasticsearch, we think there are two main problems with Elasticsearch:<p>It is not lightweight and hard to maintain a cluster<p>All of seafile tenants&#x27; data was stored in a single index and it is slow to search a file in a single library because the whole index need to be searched<p>Three years ago, we started developing a solution to solve the two problems. Rather than building a search engine from scratch, we built on top of ZincSearch, that is implemented in Go rather than JVM with a smaller runtime footprint and has Elasticsearch API compatibility, but it was still missing something that we get to find out along the way.<p>We have now open-sourced SeaSearch with the pieces we needed:<p>S3-backed Storage: Index data lives in S3. Compute nodes share the same backend, making scaling&#x2F;failover instant (no data replication needed).<p>Smart Caching: Uses a local disk cache for immutable segments to keep things fast despite the S3 backend.<p>ES API Compatible: Works as a drop-in replacement for most Elasticsearch query endpoints.<p>Lightweight Go Runtime: No JVM overhead.<p>Vector Search: Built-in support for HNSW&#x2F;IVFPQ for hybrid semantic search.<p>Hope this helps fellow devs who are stuck in this problem when building multi-tenant SaaS applications. Looking forward to your responses.

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  • 信息来源：Hacker News 新项目
  • 发布时间：2026/9/16 10:45:52