Nicheloom

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A lightweight, stateless database for agent memory

Details

External ID
49450816
Source
HN
Company
—
Product
A lightweight, stateless database for agent memory
Website domain
polign.com
Launched
Aug. 26, 2026
Cohort
—
Upvotes
36
Upvotes percentile
0.8245967741935484
Tags
—
Fetched at
Sept. 10, 2026, 5:32 a.m.
Updated at
Sept. 10, 2026, 5:32 a.m.

Description

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-memoryLive search demo: https://demo.polign.comDocs: https://polign.com

Enrichment

Theme
database infrastructure and developer tools
Vertical
Horizontal
Function
Data infrastructure
Audience
Developer
AI stance
AI feature
Project type
Commercial product
Normalized one-liner
stateless database for agent memory
Manually corrected
False

Could you build this?

Partial The user-facing API is straightforward, but designing a reliable stateless vector and BM25 index that operates efficiently directly against object storage requires deep database systems knowledge.

What it would actually take: Requires writing an embedded search engine in Rust or Go that formats data into immutable columnar and inverted-index files (similar to LanceDB or Tantivy) stored on S3/GCS. The challenging components include implementing byte-range queries over object storage, fast client-side HNSW/IVF vector indexing, and deterministic fact-conflict resolution semantics without persistent server state.

Discussion

14 comments analyzed.

Competitors mentioned: Vector databases (hosted solutions like Pinecone, Weaviate), Litestream with SQLite, Claude Code with markdown file indexing, LLM-generated custom memory systems

Concerns raised: Closed source approach is a non-starter for adoption, No clear differentiation from existing vector DB solutions, Lack of built-in observability and mutation capabilities, Keyword search limitations and ambiguity in retrieval, Cold query latency tradeoff

Feature requests: Observability and user-friendly mutation/modification interface, Open-source the core or release parts of it, Repo-aware agent memory for coding agents, Support for multiple memory types (working, procedural, semantic)

Competitors

Other products that read as similar to this one — 86 launches clear the similarity bar, closest 8 shown.

Attention rank: #20 of 87 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 281 days after the earliest competitor.

Other launches for this product

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