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Head-to-head

Overcast vs Shipyard: which should you choose in 2026?

Both improve confidence before something breaks, but they watch different layers. Overcast watches running services; Shipyard catches bad data changes before they merge. Teams that ship data products usually end up wanting both, so the useful question is which one to buy first.

Overcast logo

Overcast

Observability a two-person team can afford to run and actually understand

Open sourceOpen source1.1k upvotes
Visit Overcast
Shipyard logo

Shipyard

Deploy previews for data pipelines, so reviewers see the diff in the data

Paid731 upvotes
Visit Shipyard

Overcast vs Shipyard at a glance

Overcast and Shipyard compared attribute by attribute
AttributeOvercastShipyard
Pricing modelOpen sourcePaid
Entry priceFree tier available$49/mo
Open sourceYesNo
Self-hostableYesNo
CategoryDeveloper Tools, Open SourceDeveloper Tools
Upvotes1.1k731
Discussion142 comments44 comments
Launched20262026
VerifiedYesYes

Pros and cons

Overcast

Strengths

  • Catches failures in running services in real time
  • Open source with a genuinely usable self-hosted build
  • Predictable ingest-based pricing, no per-host charge
  • One binary — operable by a single engineer

Trade-offs

  • Will not detect silently wrong data
  • Single-node ceiling in the low terabytes per day
  • You operate it, unless you take the hosted plan

Shipyard

Strengths

  • Shows the data diff before a change merges
  • Per-repository pricing — reviewers are free
  • Works with existing dbt and SQLMesh projects unmodified
  • Production rows never leave your own warehouse

Trade-offs

  • Only helps at review time — no runtime monitoring
  • Requires a warehouse it supports
  • Sampling means very rare edge cases can still slip through

Interface comparison

Overcast interface — main workspace
Overcast
Shipyard interface — main workspace
Shipyard

The detail

The distinction that matters

Overcast answers is it up and how fast is it. Shipyard answers did this change break the numbers.

These sound adjacent and are operationally very different. A service can be perfectly healthy while emitting wrong data for a month, and no amount of latency monitoring will surface it.

Where they overlap

Both post to pull requests, both integrate with the same warehouses, and both are priced per unit of work rather than per seat. If you are running them together, Shipyard's diffs can trigger Overcast alerts on merge — the integration is a webhook, not a project.

Cost shape

Overcast is priced on ingested volume, which scales with traffic. Shipyard is priced per repository plus your own warehouse compute, which scales with how often you open pull requests. For most teams Shipyard is the smaller and more predictable line.

The verdict

Buy Overcast first if your pages come from services timing out. Buy Shipyard first if your incidents are "the dashboard has been wrong since Tuesday". If you cannot tell which, it is almost always the second one — silent data failures are the ones that go undetected longest.

More about OvercastMore about Shipyard

Overcast vs Shipyard — FAQ

Which is better, Overcast or Shipyard?

Buy Overcast first if your pages come from services timing out. Buy Shipyard first if your incidents are "the dashboard has been wrong since Tuesday". If you cannot tell which, it is almost always the second one — silent data failures are the ones that go undetected longest.

Is Overcast or Shipyard cheaper?

Overcast has the lower entry price at Free versus $49 for Shipyard. Entry price is rarely the whole story though — check how each one scales, since seat-based and usage-based pricing diverge sharply as a team grows.

Can I self-host Overcast or Shipyard?

Overcast is open source and can be self-hosted. Shipyard is a hosted product with no self-hosted option.

What are the main differences between Overcast and Shipyard?

Both improve confidence before something breaks, but they watch different layers. Overcast watches running services; Shipyard catches bad data changes before they merge. Teams that ship data products usually end up wanting both, so the useful question is which one to buy first.

Still deciding?

If neither is quite right, these pages cover the wider field.

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