olucasandrade

olucasandrade / kaptanto

Public

kaptanto captures every insert, update, and delete from Postgres and MongoDB the moment it happens — and delivers it via stdout, SSE, or gRPC. One static binary. Self-contained. Deploys anywhere.

kaptan.to
13
0
100% credibility
Found Apr 23, 2026 at 13 stars -- GitGems finds repos before they trend. Get early access to the next one.
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AI Analysis
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AI Summary

Kaptanto is a standalone Change Data Capture tool that streams real-time inserts, updates, and deletes from Postgres or MongoDB to stdout, SSE, or gRPC with no external dependencies.

How It Works

1
📖 Discover Kaptanto

You find a simple tool that captures every change in your Postgres or MongoDB database the instant it happens.

2
⬇️ Grab the single file

Download one ready-to-run file—no installs or extras needed.

3
🔧 Prep your database

Flip a quick switch in your database settings to share its changes.

4
🚀 Start with one command

Run a simple line telling it your database and tables, and watch live changes pour out.

5
Pick your stream style
📤
Console output

See changes printed right in your terminal or logs.

🌐
Web updates

Get live feeds for websites or dashboards.

🔌
App connection

Link directly to your apps or services.

✅ Changes flow safely

Every update is captured reliably, resumes perfectly after any hiccup, and you're set.

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Star Growth

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AI-Generated Review

What is kaptanto?

Kaptanto captures every insert, update, and delete from Postgres and MongoDB the moment it happens, delivering unified events via stdout, SSE, or gRPC. One static Go binary deploys anywhere—no sidecars, brokers, or runtime deps. It handles snapshots, backfills, and live streams with per-key ordering and resumable cursors.

Why is it gaining traction?

Benchmarks crush Debezium (37x throughput), Sequin, and PeerDB on steady loads and bursts, with sub-second recovery. Users get durable logs, HA failover via Postgres locks, column/row filters, and Prometheus metrics out of the box. Pipe to jq or stream directly—no Kafka needed.

Who should use this?

Backend devs syncing Postgres/Mongo data to warehouses, caches, or search indexes. Suits solo engineers or small teams building real-time apps, avoiding Debezium's JVM bloat or PeerDB's multi-service setup. Great for containerized deploys needing low-latency CDC.

Verdict

Solid for Postgres/Mongo CDC if benchmarks hold in prod—docs shine, tests are thorough. But 13 stars and 1.0% credibility scream early alpha; prototype first, don't bet the farm yet.

(178 words)

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