Nicheloom visits: 58,345 all-time · 7,637 in the last 7 days

The opportunity tracker for new startups.

Today: 1,008 launches · Niche of the day: specialized calculation tools · See what launched today →

Polynya

Turn your Postgres into workspaces for AI

Get picks like this daily. Today's launch numbers, the top launches, AI and tech news, and a daily opportunity pick, straight to your inbox.

Want to reach these readers? Sponsor an issue.

The idea is simple: AI agents need real-time data to be useful. But streaming real-time data into your data warehouse means you need the data warehouse to be up 24/7. This is expensive and wasteful. What if you could spin up an ephemeral data warehouse only when your agent needs it, and get real-time data at the same time?The solution: Polynya replicates your data into Iceberg, and gives your agent an ephemeral ClickHouse instance on demand. Polynya also provides persistent workspaces — collections of views that survive across sessions. So from your agent's point of view, it's a 24/7 data warehouse.At its core, Polynya is a data platform for streaming real-time data from Postgres to Iceberg. But instead of spending hours setting up costly and complex pipelines involving Kafka, Debezium, Flink, etc., Polynya lets you do this with just one command:npx polynya createIt's currently free on early access, so do try it out and give me any feedback! Currently there is no web dashboard yet (coming soon), you interact with it 100% through CLI.P.S. Polynya is built on top of pg2iceberg, the open source Postgres to Iceberg replication tool I've been building for the past few weeks: https://pg2iceberg.dev/

HN · launched Apr 26, 2026 · 5 upvotes (top 89%) · 0 views

Niche: cloud infrastructure and development platforms · 74 launches, 6 in the last 7 days · Explore this niche →

Category and tags

  • Horizontal
  • Data infrastructure
  • Developer
  • AI feature
  • Commercial product

Visit website ↗ Source listing ↗

Could you build this?

No Continuously streaming Postgres replication streams to Apache Iceberg and orchestrating on-demand ephemeral ClickHouse instances requires advanced distributed systems and data engineering infrastructure.

What it would actually take: The system requires a distributed change data capture (CDC) engine reading Postgres logical replication slots (WAL) and translating them into micro-batched Parquet files committed to Apache Iceberg metadata catalogs every 30 seconds. Additionally, it requires an orchestration control plane (e.g., on Kubernetes or Fly.io) that can instantly spin up and tear down isolated ClickHouse compute nodes wired to query the Iceberg object store. This requires senior expertise in database internals, CDC pipelines, analytical storage engines, and container orchestration.

Discussion

No comments on this launch.

Competitors

Other products that read as similar to this one : 146 launches clear the similarity bar, closest 8 shown.

Attention rank: #138 of 147 (itself plus its competitors, highest first, normalized so YC and Product Hunt are compared fairly).

Launched 179 days after the earliest competitor.

The niche, labels, vibe code rating and competitor comparison on this page are analysis by Nicheloom. If you use them, please credit nicheloom.com. How you may use our data.