Linking Snowplow Analytics as a source
Let AI connect your sources for you
Skip the manual setup — run this in your project and the wizard auto-detects your databases and APIs and connects them to PostHog.
This source is currently in alpha. The interface and available tables may change.
The Snowplow Analytics connector syncs pipelines, users, data models, and more into the PostHog data warehouse, so you can analyze them alongside your product data.
Prerequisites
Credentials that can read the data you want to sync. PostHog only reads data, so read access is enough.
Adding a data source
- In PostHog, go to the Sources tab of the data pipeline section.
- Click + New source and click Link next to this source.
- Enter your credentials (see Configuration below) and click Next.
- Select the tables you want to sync, choose a sync method and frequency, then click Import.
Once the syncs are complete, you can start querying this data in PostHog.
Enter your Snowplow BDP Console API credentials to pull your pipeline health and data modeling job data.
Find your Organization ID on the Console's Manage organization page, then create an API key (a key ID + key secret pair) under Console settings → API keys. Note that all Snowplow Console API keys carry admin privileges, so store them carefully.
This connector talks to the standard BDP Console host (console.snowplowanalytics.com); privately-hosted Console deployments are not supported yet.
You'll be asked for:
- Organization ID: for example
9e884a10-51c9-4632-9c05-01ba4c2b521a. - API key ID: for example
a1b2c3d4-0000-0000-0000-000000000000. - API key
Sync modes
Each table can be synced in one of several modes, depending on what the source supports:
- Webhook (when available) – the source pushes changes to PostHog in real time. Fastest freshness, lowest ongoing cost, and the only mode that reliably captures updates and deletes.
- Incremental – only new or updated rows are synced on each run, using a cursor field (such as an
updated_attimestamp). Cheaper than a full refresh, but deletes aren't captured. - Append only – new rows are appended using a cursor field; existing rows are never updated. Ideal for immutable, append-only tables like event logs.
- Full refresh – the whole table is reloaded on every sync. Use it when a table has no reliable cursor or when you need deletions reflected.
See sync methods for a full explanation of how each mode works and how to choose between them.
All Snowplow Analytics tables are full refresh. Each sync replaces the contents of the table.
Configuration
| Option | Type | Required |
|---|---|---|
Organization ID | text | Yes |
API key ID | text | Yes |
API key | password | Yes |
Supported tables
| Table | Description | Sync method | Incremental field | Primary key |
|---|---|---|---|---|
pipelines | The Snowplow pipelines in your organization. | Full refresh | — | — |
users | Users of your Snowplow BDP Console organization. | Full refresh | — | — |
data_models | Data models (dbt or SQL Runner) configured to run against your warehouse. | Full refresh | — | — |
data_structures | Data structures (event and entity schemas) registered in your organization, with the most recent deployment per environment. | Full refresh | — | — |
job_runs | Snowplow only retains job run history for about the preceding week, so historical backfill beyond that is not possible | Incremental, Full refresh | startTime | — |
job_run_steps | Snowplow only retains job run history for about the preceding week, so historical backfill beyond that is not possible | Incremental, Full refresh | runStartTime | — |
failed_event_metrics | Failed-event counts per pipeline, error, and time bucket. Snowplow keeps about a week of these aggregates | Incremental, Full refresh | window | — |
Troubleshooting
- If the connection fails with an authorization error, the API key ID is wrong, expired, or has been revoked. Create a new one, then reconnect the source.
- If a table syncs no rows, the credential may not have access to that data. Check its permissions, then reconnect the source.
If your sync is failing or data looks wrong, see the Data warehouse troubleshooting guide. If that doesn't help, contact support – we're happy to help.