Lakeloop
Show HN: analytics on Postgres without standing up a warehouse

Your Postgres, as a lakehouse — on your own S3.

Paste a Postgres URL. Lakeloop streams your tables to Parquet/Iceberg in your own S3 bucket and exposes a SQL endpoint your BI tools already speak. No warehouse to run, no per-GB storage markup.

Free tier: 1 table, daily sync. No credit card. Live in under 5 minutes.

lakeloop · connection · demo_shop
$ lakeloop connect "postgres://…@db.internal:5432/shop"
✓ connected · found 3 tables · estimated 5.6k rows

→ streaming public.orders     5,000 rows → s3://acme-lake/…/orders.parquet
→ streaming public.customers    500 rows → s3://acme-lake/…/customers.parquet

SQL endpoint ready ↓
> SELECT status, count(*), sum(amount_cents)/100.0 AS rev
  FROM orders GROUP BY 1 ORDER BY 2 DESC;

 status   │ count │   rev
─────────┼───────┼──────────
 paid     │ 3000  │ 312,665
 pending  │ 1000  │ 104,195
 refunded │ 1000  │ 104,265

Three steps. Zero ops.

From connection string to queryable lakehouse in minutes.

1 · Connect Postgres

Paste a read-only connection string. We introspect your schema and let you pick the tables to sync.

2 · Point at your S3

Bring your own bucket + keys. Data lands as Parquet (or an Iceberg catalog) — you own and pay for storage directly.

3 · Query anywhere

Use the managed SQL endpoint from Metabase, Superset, or DuckDB — or read the Parquet straight from S3.

Built for small teams who hate ops

Warehouse economics without the warehouse.

Bring-your-own-S3

Storage cost stays on your AWS bill at raw S3 rates — no per-GB markup, no data hostage situation. Your bucket, your data.

Hourly CDC

Pro plans keep tables fresh every hour using change-data-capture, so dashboards aren't a day stale.

Read-only & encrypted

We connect read-only and encrypt your credentials at rest with AES-256-GCM. The SQL endpoint is sandboxed.

Iceberg catalog

On Scale, get a real Apache Iceberg catalog — time travel, schema evolution, and engine portability.

DuckDB-fast

Columnar Parquet + a vectorized engine means analytical queries run in milliseconds, not minutes.

BI-tool native

A standard SQL endpoint drops into the tools your team already uses. No new query language to learn.

Simple, honest pricing

You pay Lakeloop for the connector. You pay AWS for storage. Nobody marks up your bytes.

Free

Kick the tires on one table.

$0/mo

No credit card required

  • 1 table
  • Daily sync
  • Parquet on your own S3 (or managed local)
  • SQL endpoint for BI tools
  • Community support
Current plan
Most popular

Pro

For a small team that needs fresh data.

$39/mo

≈ ₹3,300/mo

  • 10 tables
  • Hourly CDC sync
  • Bring-your-own S3 bucket
  • SQL endpoint + query history
  • Email support
Choose Pro

Scale

Unlimited tables with a real Iceberg catalog.

$99/mo

≈ ₹8,300/mo

  • Unlimited tables
  • Hourly CDC sync
  • Iceberg catalog (time travel, schema evolution)
  • Bring-your-own S3 bucket
  • Priority support
Choose Scale

Stop paying warehouse prices for small data.

Connect your first table free and have a queryable lakehouse before your coffee gets cold.

Get started free