redskyluan

5개월 전discuss

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

redskyluan

5개월 전discuss

  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

6개월 전discuss

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

redskyluan

9개월 전discuss

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

9개월 전discuss

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

9개월 전discuss

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

redskyluan

11개월 전discuss

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

11개월 전discuss

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

11개월 전discuss

Curious—why the shift from a Milvus-compatible API to a Chroma-compatible one? And of course, something in Python… because that’s obviously the fastest way to conquer the world.

redskyluan

12개월 전discuss

Code Context is an MCP plugin that brings semantic code search to Claude Code, Gemini CLI, or any AI coding agent.

Full codebase indexing means richer context and better code generation.

100% open-source.

redskyluan

작년discuss

Same as cursor, We update every 5 minutes. You can pick a local storage or using cloud services for sure

redskyluan

작년discuss

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

작년discuss

Also let us know your ideas! How do we make code search easier

redskyluan

작년discuss

Most vector database benchmarks today focus on toy use cases: static data, pure ANN search, no filters, no writes.

That’s not how things work in production.

We built VectorDBBench to benchmark vector databases under real-world conditions. It’s open source and just hit v1.0.0.

What’s new in v1.0.0:

Label Filtering + vector search tests

Concurrent read/write under pressure

Customer dataset

Better webUI

It supports several popular vector DBs out of the box (Milvus, Weaviate, Qdrant, Chroma, etc.) and is easy to extend.

If you’re building anything with RAG, embeddings, or search infra, we’d love feedback.

redskyluan

작년discuss

Amazing, seeking for similar service for years

redskyluan

작년discuss

Sharding is such a pain and no company should have to endure that.

redskyluan

작년discuss

What’s the largest deployment you’ve maintained in production?

If you’ve had the chance to manage one—especially while handling concurrent insert and search operations—you’ve probably felt the pain firsthand and understand just how critical scalability really is.

Insert into PGvector is super slow when data accumulate and the index build will take forever

redskyluan

작년discuss

sharding is a bad solution for any databases, especially vector database. See https://milvus.io/blog/why-manual-sharding-is-a-bad-idea-for...

redskyluan

작년discuss

Try ollama? It support several embedding models

redskyluan

작년discuss

Sharding can hinder your business growth, especially for all AI startups.

Prepare for scalability with a non-sharded architecture from the start.