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Show HN: SeaSearch – Lightweight, S3-backed multi-tenant search engine

Hacker News - Tue, 09/15/2026 - 10:45pm

Hi HN, I'm Daniel, co-founder of Seafile.

I'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.

After years of using Elasticsearch, we think there are two main problems with Elasticsearch:

It is not lightweight and hard to maintain a cluster

All of seafile tenants' 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

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.

We have now open-sourced SeaSearch with the pieces we needed:

S3-backed Storage: Index data lives in S3. Compute nodes share the same backend, making scaling/failover instant (no data replication needed).

Smart Caching: Uses a local disk cache for immutable segments to keep things fast despite the S3 backend.

ES API Compatible: Works as a drop-in replacement for most Elasticsearch query endpoints.

Lightweight Go Runtime: No JVM overhead.

Vector Search: Built-in support for HNSW/IVFPQ for hybrid semantic search.

Hope this helps fellow devs who are stuck in this problem when building multi-tenant SaaS applications. Looking forward to your responses.

Comments URL: https://news.ycombinator.com/item?id=49721546

Points: 2

# Comments: 2

Categories: Hacker News

Ask HN: Shifting Reoccuring Agentic Workflow to ML Process?

Hacker News - Tue, 09/15/2026 - 10:31pm

I know I can simply ask myaAgent or Google this question but would prefer to ask HN for any practical real examples used day to day.

Question: For the people who build agentic workflows, how do I implement a ML habit where the agent learns from itself, can iterate and improve on it's own? I would still oversee and validate but would love to learn ML implementation to agents. Am I just overthinking this and can write it in the prompt? Any help is appreicated!

Comments URL: https://news.ycombinator.com/item?id=49721483

Points: 1

# Comments: 1

Categories: Hacker News

Sony SMC-70

Hacker News - Tue, 09/15/2026 - 10:30pm
Categories: Hacker News

Marginalia Search

Hacker News - Tue, 09/15/2026 - 9:06pm

Article URL: https://marginalia-search.com/

Comments URL: https://news.ycombinator.com/item?id=49720957

Points: 1

# Comments: 0

Categories: Hacker News

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