The Flat-Rate dbt Cloud Alternative
Hosted dbt-core
dagctl runs your dbt-core project in production — scheduling, compute, monitoring, and autonomous failure recovery — for one flat rate with no per-seat fees and no run quotas.
Everything dbt-core needs to run in production
You chose dbt-core to avoid per-seat pricing. dagctl gives it production infrastructure without giving that up.
No per-seat fees, no run quotas
dbt Cloud charges per developer seat and meters your runs. dagctl charges one flat rate: your whole team gets access, every model runs on schedule, and the bill is the same every month.
Scheduled runs
Cron-based schedules with retries and Slack alerts. No Airflow, Dagster, or Prefect to deploy and maintain.
Compute & infrastructure
Isolated Kubernetes compute per organization. No clusters to provision, patch, or scale.
Git integration
Connect your repository and deploy on every merge. Your dbt project stays in your repo, under your review process.
Warehouse connections & secrets
Encrypted credentials for your warehouse with file-mount support. No Vault or Secrets Manager integration to build.
Monitoring & streaming logs
Every run with real-time logs, execution history, and per-model timing. When something is slow or broken, you see exactly where.
Lineage & catalog
Interactive DAG visualization and a cross-project catalog of models, columns, and metadata.
Your pipeline breaks at 2am. The fix is already waiting.
When a scheduled dbt-core run fails, dagctl does not just page you. An autonomous agent diagnoses the failure, writes the fix, and opens a pull request in your repository — you review and merge through your normal workflow. That is the difference between an alert and a resolution.
How dagctl compares
Self-hosting, dbt Cloud, and dagctl side by side
| Capability | Self-Hosted | dbt Cloud | dagctl |
|---|---|---|---|
| Supported frameworks | Any (you host it) | dbt only | SQLMesh and dbt-core |
| Pricing model | Infrastructure costs | Per-seat + run quotas | Flat rate, users included |
| Infrastructure | You manage clusters or VMs | Managed | Managed |
| Job scheduling | Airflow, Dagster, or cron | Built-in | Built-in with Slack alerts |
| Failure recovery | You debug at 2am | Alerts only | Fix opened as a PR |
| Secret management | Vault, SSM, or DIY | Built-in | Built-in with file-mount support |
| Monitoring & logs | Grafana, Datadog, or ELK setup | Built-in | Built-in, real-time streaming |
| Model catalog | Build or buy separately | dbt Explorer | Included, cross-project |
| DAG visualization | Framework CLI only | Built-in | Built-in, interactive |
| RBAC & SSO | DIY with your identity provider | Built-in (Enterprise tier) | Built-in RBAC, SSO on Professional |
Flat-rate pricing
dbt Cloud pricing grows with every seat you add. dagctl is one number: unlimited users, unlimited models, no run quotas.
Starting at
$999/mo
flat rate — unlimited users and models
- Flat Rate — No per-seat or consumption fees
- Same-Day Setup — From git repo to production
- Fully Managed — We handle the infrastructure
- Unlimited Models — No per-model charges
Frequently Asked Questions
What is a good dbt Cloud alternative?
dagctl is a dbt Cloud alternative built for teams running dbt-core. It provides hosted scheduling, compute, monitoring, and autonomous failure recovery for a flat monthly rate — no per-seat fees and no run quotas. It also runs SQLMesh natively, which dbt Cloud does not.
Can I run dbt-core in production without dbt Cloud?
Yes. dbt-core is open source, and dagctl provides the production infrastructure around it: connect your git repository and dagctl handles scheduled runs, compute, secrets, monitoring, and failure recovery. You keep dbt-core and skip the per-seat pricing.
How much does hosted dbt-core cost?
dagctl starts at $999 per month as a flat rate that includes unlimited users and unlimited models. There are no per-seat fees and no run quotas, so the bill does not grow with your team.
What happens when a scheduled dbt run fails?
dagctl alerts you immediately, and its autonomous remediation agent diagnoses the failure, writes a fix, and opens a pull request in your repository. You review and merge through your normal code-review workflow — the fix is waiting for you instead of a stack trace.
Does dagctl support dbt packages and custom macros?
Yes. dagctl runs your dbt-core project as it exists in your git repository, including packages, macros, seeds, snapshots, and tests.
Which data warehouses does dagctl support for dbt-core?
dagctl runs dbt-core projects against Snowflake, BigQuery, Databricks, Redshift, PostgreSQL, and DuckDB.
How do I migrate from dbt Cloud to dagctl?
Your dbt project already lives in a git repository, so migration is connecting that repository to dagctl, configuring your warehouse credentials, and recreating your job schedules. Most teams are running in production the same day.
Ready to stop paying per seat for dbt?
Deploy your dbt-core project to production in a day. We run the infrastructure, scheduling, and failure recovery.