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PostHog is a product analytics platform for tracking user behavior, product usage, and event-level activity. The Nekt PostHog connector extracts project metadata and event data into your Catalog so you can analyze product engagement at scale.

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Configuring PostHog as a Source

In the Sources tab, click on the “Add source” button located on the top right of your screen. Then, select the PostHog option from the list of connectors. Click Next and you’ll be prompted to add your access.

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1. Add account access

The following configurations are available:
  • Personal API key: Personal API key used to authenticate against the PostHog API. See the official PostHog API docs.
  • Base URL: API base URL for your PostHog region or self-hosted environment.
    • US Cloud: https://us.posthog.com
    • EU Cloud: https://eu.posthog.com
    • Self-hosted: your own PostHog domain
  • Start date: Earliest date from which events are synced.
Event payloads can be large. Choosing a very old start date may significantly increase the first sync duration.
Once you’re done, click Next.

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2. Select streams

Choose which data streams you want to sync. For faster extractions, select only the streams relevant to your analysis.
Tip: In addition to the projects stream, the connector creates one dynamic event stream per PostHog project using the pattern {organization_slug}_events_{project_name}.
Select the streams and click Next.

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3. Configure data streams

Customize how you want your data to appear in your catalog. Select the desired layer where the data will be placed, a folder to organize it inside the layer, a name for each table, and the type of sync.
  • Layer: Choose the layer where extracted PostHog tables will be created.
  • Folder: Optionally group all PostHog tables inside a folder.
  • Table name: A default name is suggested, but you can customize it and optionally apply a prefix.
  • Sync Type: Choose between INCREMENTAL and FULL_TABLE.
    • Incremental: Recommended for event streams, using timestamp as the replication key.
    • Full table: Suitable for projects metadata refreshes.
Once you are done configuring, click Next.

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4. Configure data source

Describe your data source for easy identification within your organization, not exceeding 140 characters. To define your Trigger, consider how often your product analytics data should be refreshed. Optionally, you can define:
  • Delta Log Retention: How long Nekt keeps previous table states. See Resource control.
  • Additional Full Sync: Periodic full syncs to complement incremental runs.
When you are ready, click Next to finalize the setup.

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5. Check your new source

You can view your new source on the Sources page. If needed, manually trigger the extraction by clicking on the arrow button. Once a run completes successfully, your data appears in the Catalog.
You need at least one successful source run to see the tables in your Catalog.

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Streams and Fields

Below you’ll find the available PostHog streams and their core fields.
Project metadata for each organization available to the API token.Key fields:
  • id - Project identifier (primary key)
  • uuid - Project UUID
  • organization - Organization identifier linked to the project
  • name - Project name
  • api_token - Project ingestion token
  • timezone - Project default timezone
  • is_demo - Indicates whether the project is a demo project
  • ingested_event - Indicates whether at least one event has been ingested
  • completed_snippet_onboarding - Onboarding status for snippet setup
  • has_completed_onboarding_for.feature_flags - Feature flags onboarding status
  • access_control - Access-control enablement flag
Notes:
  • Stream name: projects
  • Primary key: id
  • Replication: full-table style (no replication key)
Event-level analytics data from each PostHog project. The connector dynamically creates one stream per project discovered during catalog discovery.Dynamic stream naming:
  • {organization_slug}_events_{project_name} (slugified with underscores)
Key fields:
  • id - Event identifier
  • distinct_id - User or actor distinct identifier
  • event - Event name
  • timestamp - Event timestamp (replication key)
  • properties - Array of key/value event properties
  • person.is_identified - Whether associated person is identified
  • person.distinct_ids - Associated person distinct IDs
  • person.properties.email - Associated person email (when available)
  • elements - Captured element metadata
  • elements_chain - Serialized captured element chain
Notes:
  • Primary keys: id, distinct_id
  • Replication key: timestamp
  • Incremental sync uses start_date for the first run, then continues from saved state

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Data Model

The connector follows an organization/project-based model:

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Use Cases for Data Analysis

This section includes practical SQL examples you can run in Explorer.

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1. Event volume by day

Measure daily event volume to track product activity trends. 
SELECT
   DATE(CAST(timestamp AS timestamp)) AS event_date,
   event,
   COUNT(*) AS total_events,
   COUNT(DISTINCT distinct_id) AS unique_users
FROM
   nekt_raw.posthog_org_events_project
GROUP BY
   1,
   2
ORDER BY
   event_date DESC,
   total_events DESC;

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2. Top users by event activity (last 30 days)

Identify the most active users based on tracked events. 
SELECT
   distinct_id,
   COUNT(*) AS event_count,
   MIN(CAST(timestamp AS timestamp)) AS first_event_at,
   MAX(CAST(timestamp AS timestamp)) AS last_event_at
FROM
   nekt_raw.posthog_org_events_project
WHERE
   CAST(timestamp AS timestamp) >= current_timestamp - interval '30' day
GROUP BY
   1
ORDER BY
   event_count DESC
LIMIT 100;

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Skills for agents

Download PostHog skills file

PostHog connector documentation as plain markdown, for use in AI agent contexts.