Hacker News: anuptalwalkar

New comment by anuptalwalkar in "Show HN: A lightweight, stateless database for agent memory"

anuptalwalkar — Thu, 27 Aug 2026 23:59:23 +0000

The policy layer you’re describing lives in the harness, and yes, it changes over time. What I wanted to showcase is polign_db underneath with typed records, hybrid index, attached to your bucket. You can swap your memory design without migrating the storage or spawn nodes to access it quickly.

I see your point on observability. I haven’t baked it into polign yet, but I have been thinking about ‘how’ I would do it a very user friendly way. Glad to have a conversation about it.

New comment by anuptalwalkar in "Small Models Have Arrived"

anuptalwalkar — Thu, 27 Aug 2026 21:55:30 +0000

I kind of agree with your assessment. Running models not just on local, but cheap and lightweight frameworks will drive the next phase.

Not trying to plug, but I do't know any other way. I wrote a piece couple of days ago on small models and memory usage on the edge devices- https://polign.com/blog-edge-agent-memory and https://news.ycombinator.com/item?id=49450816 closing on the same problem.

New comment by anuptalwalkar in "Show HN: A lightweight, stateless database for agent memory"

anuptalwalkar — Thu, 27 Aug 2026 19:26:54 +0000

Thanks, is the concern being non-starter on the trust side? the binary makes zero outbound calls. It talks to your bucket and nothing else, and that's verifiable with egress monitoring. I'm putting up a security page that spells it out.

Open-sourcing parts of it isn't off the table. I kept the core closed for now to understand the interest in it.

New comment by anuptalwalkar in "Show HN: A lightweight, stateless database for agent memory"

anuptalwalkar — Thu, 27 Aug 2026 19:14:13 +0000

When I started, I was using what was available out in the world. The vector dbs I used and even the first version I built weren't really optimized to use RAM and resources conservatively. One of the aspects of Polign is it's optimized towards cold queries and only warms the cache when needed, all while keeping the recall accuracy in acceptable range. I accepted slower first-query latency on cold data as the tradeoff. For example, the demo serves 12.5 million passages from S3 with the server idling around 37 MiB RSS (I realized there is a 20 MB gcp sdk in there).

Hosted db have query costs that grow with the corpus, and self hosted have operational overheads. They do add up over time and I wanted cost flat, which took a while to get it right.

If a vibe-coded version covers your use case, you don't need this. I have added my own experience working and optimizing the storage into this, and Im certain it holds up well for a growing corpus and with simplicity to use it across multiple readers.

New comment by anuptalwalkar in "Show HN: A lightweight, stateless database for agent memory"

anuptalwalkar — Thu, 27 Aug 2026 18:02:01 +0000

It's wordplay. I wanted it to be lightweight like pollen, but carrying all the information you need to build on top of it. The 'align' part nods to the core vector search aligning with your queries.

New comment by anuptalwalkar in "Show HN: A lightweight, stateless database for agent memory"

anuptalwalkar — Thu, 27 Aug 2026 05:00:16 +0000

Thanks for taking a look. Yes, I kept it closed source for now. I'll mention that on the page.

Litestream with SQLite would solve some of these use cases, and backing up to S3 or GCS works well.

Here I was focused on more dynamic workloads. For example, larger indexes and corpus that can be accessed by multiple readers. I didn't want to invest in local storage, so the data is made to stay cold until it's actually accessed into warm cache.

Also, one node can serve all of that in one collection while serving typed agent memory in another.

Perhaps I missed something, but storage, memory, and operational overhead is something I wanted to worry less about.

Show HN: A lightweight, stateless database for agent memory

anuptalwalkar — Wed, 26 Aug 2026 15:24:51 +0000

I've been working on Polign and built a small prototype around something I've been thinking about with agent memory. I have built a lightweight/stateless vector db + BM25 search which works really well with typed facts and structured queries.

It uses your own S3, or GCS bucket as primary storage, and restarting a node is fairly quick.

Demo + writeup: https://polign.com/blog-edge-agent-memory

Live search demo: https://demo.polign.com

Docs: https://polign.com

Comments URL: https://news.ycombinator.com/item?id=49450816

Points: 30

# Comments: 11