redskyluan

5 bulan yang laludiscuss

Between Claude Code and my wife, only one enjoyed my late nights — a fun take on vibe-coding obsession and hard engineering lessons.

redskyluan

5 bulan yang laludiscuss

  Maintainer of Milvus here. A few thoughts from someone who lives this every day:

  1. The free user problem is real, and AI makes it worse. We serve a massive community of free Milvus users — and we're grateful for them, they make the project what it is. But we also feel the tension MinIO is describing. You invest serious engineering effort into stability and bug fixes, and most users will never become paying customers. In the AI era this ratio only gets harder — copy with AI becomes easier than ever

  2. We need better object storage options. As a heavy consumer of object storage, Milvus needs a reliable, performant, and truly open foundation. RustFS is a solid candidate — we've been evaluating it seriously. But we'd love to see more good options emerge. If the ecosystem can't meet our needs long-term, we may have to invest in building our own.

  3. Open source licensing deserves a serious conversation. The Apache 2.0 / Hadoop-era model served us well, but cracks are showing. Cloud vendors and AI companies consume enormous amounts of open-source infrastructure, and the incentives to contribute back are weaker than ever. I don't think the answer is closing the source — but I also don't think "hope enterprises pay for support" scales forever. We need the community to have an honest conversation about what sustainable open source looks like in the AI era. MinIO's move is a symptom worth paying attention to.

redskyluan

6 bulan yang laludiscuss

Using Hierarchical Clustering significantly reduces recall; this is a solution we used and abandoned three years ago.

redskyluan

8 bulan yang laludiscuss

dude you already missed the window.

nothing is better than sqlite as a library and don't use high perforamnce as your value for a python product

redskyluan

8 bulan yang laludiscuss

I really enjoyed this article. I have a lot of appreciation for PG, but some articles tend to exaggerate its capabilities, especially when it comes to PG vectors, which can be off-putting."

redskyluan

8 bulan yang laludiscuss

check https://github.com/zilliztech/VectorDBBench

redskyluan

10 bulan yang laludiscuss

By the way, if you’re not fully satisfied with S3Vector’s write, query, or recall performance, I’d encourage you to take a look at what we’ve built with Zilliz Cloud. It may not always be the lowest-cost option, but it will definitely meet your expectations when it comes to latency and recall.

redskyluan

10 bulan yang laludiscuss

Author of this article.

Yes, I’m the founder and maintainer of the Milvus project, and also a big fan of many AWS projects, including S3, Lambda, and Aurora. Personally, I don’t consider S3Vector to be among the best products in the S3 ecosystem, though I was impressed by its excellent latency control. It’s not particularly fast, nor is it feature-rich, but it seems to embody S3’s design philosophy: being “good enough” for certain scenarios.

In contrast, the products I’ve built usually push for extreme scalability and high performance. Beyond Milvus, I’ve also been deeply involved in the development of HBase and Oracle products. I hope more people will dive into the underlying implementation of S3Vector—this kind of discussion could greatly benefit both the search and storage communities and accelerate their growth.

redskyluan

tahun laludiscuss

Postgres users often hit scaling issues — whether it's with LISTEN/NOTIFY, PGVector, or even basic relational queries.

For startups, Postgres is a fantastic first choice. But plan ahead: as your workload grows, you’ll likely need to migrate or augment your stack.

redskyluan

2 tahun yang laludiscuss

Regarding scale, PostgreSQL may not cover all bases. Though I'm a PostgreSQL fan, I prefer specialized services for specific tasks. Using PG-based plugins could help, but a dedicated SQL-compatible database is often a better fit.

For vector retrieval, going with a database like Milvus, designed for vectors, is usually more efficient and cost-effective. Similar principles apply across domains. Is there any vectordb under PG format?

What if we've got a deeply customized distributed vector search service on PostgreSQL, that's impressive!

redskyluan

Submissions

My Notes After Databricks Data and AI Summit 2026

Introduce Loon: lake-native storage engine behind Milvus 3.0 for AI data

Between Claude Code and my wife, only one enjoyed my late nights

My Wife Wanted Dior. I Spent $600 on Claude Code to Vibe-Code Database Instead

comments