How does Kondado replicate Sympla data to PostgreSQL?

Kondado connects directly to the Sympla API to extract your event data, then automatically loads it into your specified PostgreSQL database. The platform handles schema creation and updates, ensuring that fields like event dates and order values maintain proper data types for accurate SQL querying.

What specific Sympla information can I replicate to PostgreSQL?

You can replicate three main pipelines: Events data including names and publication status, Participants data containing emails and ticket identifiers, and Orders data with transaction details and approval dates. This covers the complete event lifecycle from registration through payment.

How frequently does my Sympla data update in PostgreSQL?

You control the update frequency through Kondado's scheduling options, selecting intervals that match your analytics needs from near-real-time updates to daily batches. This ensures your PostgreSQL database reflects the latest ticket sales and registrations without manual intervention.

Can I combine Sympla event data with other business sources in PostgreSQL?

Yes, once your Sympla data resides in PostgreSQL, you can join it with information from additional sources like MySQL, Excel, or Amazon S3 that you also replicate through Kondado. This enables unified reporting across marketing campaigns, financial systems, and attendance metrics in a single SQL environment.

What format does Sympla data take when stored in PostgreSQL?

Kondado creates structured relational tables in PostgreSQL for each pipeline, with standard PostgreSQL data types for dates, currency values, and text fields. The schema preserves relationships between events, participants, and orders so you can write joins and aggregations using standard SQL syntax.

Do I need technical skills to send Sympla data to PostgreSQL?

No coding is required to establish the connection: you simply authenticate your Sympla account and select your PostgreSQL destination through Kondado's interface. The platform manages the technical complexity of API connections and data type mapping automatically.

Can I visualize Sympla data from PostgreSQL in dashboard tools?

Absolutely, once your data reaches PostgreSQL, you can connect visualization tools like Power BI , Looker Studio , or Google Sheets to create custom reports. This flexibility lets you build event performance dashboards that update automatically as Kondado refreshes your Sympla data.

How do I track ticket sales trends from Sympla in PostgreSQL?

Use the Orders pipeline to replicate transaction data including approval dates and total values, then write SQL queries to calculate daily revenue, identify peak sales periods, and compare performance across different events. You can also join this with the Participants pipeline to analyze average order values per attendee segment.

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Send Sympla Data to PostgreSQL Automatically

To send Sympla data to PostgreSQL, connect your Sympla account as a data source in Kondado, select your PostgreSQL database as the destination, and choose which pipelines to replicate. Kondado handles the data extraction and loading automatically on your preferred schedule, eliminating manual CSV exports and complex API development work. Your event management information flows directly into PostgreSQL where you can run complex SQL queries and build comprehensive analytics.

Kondado provides a direct connection between Sympla and PostgreSQL, replicating Events, Participants, and Orders data on a configurable schedule ranging from every 5 minutes to daily, enabling automated event analytics without coding.

Once configured, Kondado maintains your PostgreSQL database with fresh Sympla data, allowing you to combine ticket sales information with other business datasets for deeper insights. Marketing teams can track campaign performance against registration numbers, finance teams can monitor revenue patterns across multiple events, and operations managers can analyze attendance trends, all using the familiar SQL environment of PostgreSQL alongside visualization tools like Power BI or Looker Studio.

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Available Sympla Data in PostgreSQL

With the Events pipeline, you can analyze which event types generate the highest attendance rates by querying start dates, end dates, and publication status directly in PostgreSQL. The Participants pipeline delivers attendee details including emails and unique ticket identifiers, enabling you to build custom segmentation lists and track individual buyer journeys across multiple events. Meanwhile, the Orders pipeline brings transaction data such as approval dates, status values, and total order values into your database, allowing finance teams to calculate revenue recognition and identify purchasing patterns without switching between platforms.

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Sympla data available for PostgreSQL

available pipelines

extractable fields

Available integrations

Integration	Description
Events	Includes information such as event name, start and end dates, and whether it is published or canceled.
Participants	Contains data about participants, including last name, email, and unique ticket identifier.
Orders	Presents order details such as status, approval date, and total order value.

Events

Includes information such as event name, start and end dates, and whether it is published or canceled.

Participants

Contains data about participants, including last name, email, and unique ticket identifier.

Orders

Presents order details such as status, approval date, and total order value.

See all available data →

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How to send Sympla data to PostgreSQL

Sync data automatically — no code, no manual exports.

Connect Sympla to Kondado

Authenticate your Sympla account in Kondado by providing your API credentials, allowing the platform to access your event management data.

Configure PostgreSQL Destination

Enter your PostgreSQL connection details including host, database name, and credentials to establish the target location for your replicated data.

Select Pipelines and Schedule

Choose which Sympla pipelines to replicate, such as Events, Participants, or Orders, and set your preferred update frequency to keep your PostgreSQL database current.

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