CDP
Hooktopus vs Segment.
Segment is built around product analytics (track/identify). Hooktopus is built around arbitrary webhooks.
Hooktopus $19 · Segment (Team 100k MTU) $120/mo + per-event fees
The honest version
When each tool is right.
Use Segment
When workflow flexibility matters more than per-event cost.
You ship a product and want to track user behavior with a CDP SDK. Identity resolution, audience syncing, reverse ETL — Segment is the leader here.
Use Hooktopus
When the job is webhook → BigQuery, full stop.
You just need to land webhooks from Stripe, Shopify, GitHub, or your own app in BigQuery. No SDKs to install.
Feature by feature
What each tool ships.
| Feature | Hooktopus | Segment |
|---|---|---|
| Pricing model | Tiered, $0–$299/mo | Per-MTU + per-event |
| Cost for 100k events / mo | $19 | ~$120+/mo (Team) |
| Event shape | Arbitrary JSON webhooks | track() / identify() / page() shape |
| BigQuery native JSON type | Yes | Yes, but Segment-shaped |
| dbt model generation | Yes | No — but dbt package exists |
| Schema drift alerts | Yes | Schema enforcement on track() events only |
| Identity resolution | No | Yes — flagship feature |
| Audiences / reverse ETL | No | Yes (Segment Personas) |
| Replay | Yes — R2-backed | Yes — Replay add-on |
The truth
Both tools can be right.
Segment is excellent at product analytics. We do the messy middle: arbitrary webhooks from SaaS sources you don't control. We complement each other.
What you get with Hooktopus
The opinionated short list.
Built for the analytics engineer
The buyer we serve is the AE who lives in dbt + BigQuery + Hex/Metabase. Our defaults match that shape.
Tiered, predictable pricing
Plan tiers, not metered. You always know your bill. Hard cap blocks writes but never loses events.
dbt-first, not dbt-bolt-on
Hooktopus generates the SQL and the sources YAML. It's the only competitor where dbt is part of the install, not the support docs.
Switch or evaluate
Migration takes about 15 minutes.
Start a free workspace, paste a Segment-compatible URL into your source, and check BigQuery. No migration tools required.