Nicheloom

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T4

a versioned datastore with branching and time-travel (S3-backed)

Details

External ID
47742167
Source
HN
Company
β€”
Product
T4
Website domain
github.com
Launched
April 12, 2026
Cohort
β€”
Upvotes
7
Upvotes percentile
0.38817480719794345
Tags
β€”
Fetched at
Sept. 7, 2026, 9:26 p.m.
Updated at
Sept. 7, 2026, 9:26 p.m.

Description

Hi HN,I built t4, a datastore that stores its WAL and snapshots in S3.Instead of traditional storage, it writes append-only segments to object storage and reconstructs state from checkpoints + WAL.A side effect of this model is that the database becomes naturally versioned: you can restore any past state, branch from any point (with copy-on-write) and replay historyI started this as an experiment to replace etcd in Kubernetes, but it’s evolving into a general-purpose versioned state store.Curious what people think about it and appreciate any feedback!

Enrichment

Theme
Vertical
Horizontal
Function
Data infrastructure
Audience
Developer
AI stance
Not AI
Project type
Commercial product
Normalized one-liner
versioned datastore with branching
Manually corrected
False

Could you build this?

No Designing a reliable ACID-compliant, branching, time-travel datastore backed by S3 with write-ahead logs, checkpointing, and cache invalidation requires advanced distributed systems and database engine expertise.

What it would actually take: Building this requires a custom storage engine written in Rust or Go implementing an LSM-tree or append-only segment log architecture integrated with an S3 object store. The difficult technical challenges involve distributed consensus, high-concurrency WAL flushing, handling S3 eventual consistency/latencies, zero-copy snapshot compaction, and transactional isolation during branching. It demands specialized distributed systems engineering that AI prompting cannot architect or verify for correctness.

Discussion

2 comments analyzed.

Feature requests: Node.js client support, Python client support

Competitors

Other products that read as similar to this one — 57 launches clear the similarity bar, closest 8 shown.

Attention rank: #39 of 58 (itself plus its competitors, highest first — normalized so YC and Product Hunt are compared fairly).

Launched 162 days after the earliest competitor.

Other launches for this product

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