PostgreSQL
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PostgreSQL serves as your primary source of behavioral truth, while Planhat acts as your system of execution. By connecting these platforms, you transform raw database rows into actionable time-series signals—including User Activities and Custom Metrics—to drive objective Health Scores and adoption monitoring. This integration ensures that commercial teams act on actual product behavior in near real-time, rather than relying on anecdotal feedback or manual queries.
Unlock the power of PostgreSQL with planhat
Improve net revenue retention
Defend recurring revenue using actual product behavior. Planhat pulls time-series usage rows from PostgreSQL and maps them to Companies and End Users, allowing commercial teams to execute earlier intervention the moment core feature adoption drops.
Shorten time to value
Measure implementation success with hard data. By mapping PostgreSQL rows to User Activities, implementation teams track initial logins and feature clicks to objectively verify when an account completes onboarding milestones.
Increase process governance
Maintain strict operational control over data pipelines. Operations teams configure Planhat to fetch PostgreSQL data incrementally using a unique numeric key, ensuring high-volume usage events sync reliably without duplications or manual query intervention.
Improve commercial predictability
Base revenue forecasts on objective adoption metrics. Planhat connects raw PostgreSQL usage tables directly to your commercial models—including Assets and Projects—translating database events into concrete health updates and predictable account follow-through.
how it works
Flow & configuration
Secure database authentication
Authorized users establish the connection in the Integrate tab by providing the hostname, port, database name, schema, and credentials. Planhat requires SSL by default to ensure secure transport of your behavioral data and supports IP allowlisting for outbound requests to your infrastructure.
Define mapping and ingestion models
Select the target table and choose whether data lands in Planhat as granular User Activities (metrics tied to specific individuals like feature clicks) or aggregated Custom Metrics (tied to Companies, Assets, or Projects). This integration is purpose-built for time-series usage data and is not intended for syncing static CRM records.
Configure the unique incrementing sync key
Specify a unique, incrementing numeric column—such as a serial ID or unix timestamp—that Planhat uses to identify which rows have not yet been synced. This mechanism enables efficient incremental polling, ensuring that high-volume event streams land in Planhat without creating duplicate records or impacting database performance.
Set the execution cadence and batch limits
Establish a scheduled cadence for data retrieval, with frequency options ranging from every five minutes to once daily at a specific hour. Admins can also define batch sizes to manage the volume of records processed during each interval. Once saved, Planhat pulls the latest event stream automatically, surfacing ingestion status in the Logs tab and making data available in Data Explorer for real-time analysis.
How secure is the connection between PostgreSQL and Planhat?
How do you map relational PostgreSQL data to Planhat's account model?
How does Planhat ensure high performance and low database load?
How can raw PostgreSQL rows be operationalized into system of action workflows?
Why sync PostgreSQL to Planhat if we already have BI tools like Tableau or Power BI?
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