No-code pipeline · Pipefy → Amazon S3

Send data from Pipefy to Amazon S3

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From Pipefy to Amazon S3: managed, scheduled, no code.

Kondado automatically replicates Pipefy Cards, Databases, Organizations, Phases, and Pipes data to Amazon S3 on a user-configured schedule, enabling seamless workflow analytics without manual exports.

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Send Pipefy Data to Amazon S3 Automatically

Sending Pipefy data to Amazon S3 requires no coding when you use Kondado’s automated data platform. Simply connect your Pipefy account as a data source, select Amazon S3 as your destination, and choose which pipelines to replicate from the available options. Kondado handles the data extraction and loads your Pipefy information into S3 buckets on a configurable schedule, whether you need updates every 5 minutes, hourly, or daily batches.

Once your Pipefy data lands in Amazon S3, you can query it directly using Amazon Athena, Presto, or Dremio for advanced analytics and data virtualization. This setup allows you to combine process management data from Pipefy with other business information stored in your data lake, creating comprehensive reports that track workflow efficiency, card completion rates, and phase durations across HR, Finance, and Customer Service departments.

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With the Cards pipeline, you can analyze completion trends and identify bottlenecks in your workflows by querying card creation dates and status changes directly in Amazon S3. The Phases pipeline provides granular data about duration spent in each workflow stage, enabling you to optimize process efficiency and reduce cycle times across departments. By combining these Pipefy datasets in your S3 data lake with information from other sources, you build custom dashboards that reveal operational insights and automate reporting for stakeholders who rely on Power BI or Looker Studio.

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Replicated to Amazon S3

Pipefy data available for Amazon S3

Tables Kondado writes into your Amazon S3, on a schedule you control.

available pipelines

185

extractable fields

Amazon S3

Destination

Available integrations

Cards

Contains information about cards, including ID, title, creation date, and completion status.

Databases

Stores entity data with ID, update timestamp, and replication information.

Organizations

Includes details about organizations, such as ID, name, and contact information.

Phases

Describes the phases of the process, with ID, name, and duration in each phase.

Pipes

Represents the pipes used, including ID, name, and status of the processes.

See all available data → Send Pipefy to Amazon S3 →

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How to send Pipefy data to Amazon S3

Sync data automatically — no code, no manual exports.

Connect Pipefy to Kondado

Authenticate your Pipefy account by providing your API credentials through Kondado's interface to establish the data source connection.

Configure Amazon S3 Destination

Enter your S3 bucket details and authentication keys to set up the destination where your Pipefy datasets will be stored and organized.

Select Pipelines and Schedule

Choose which pipelines to replicate from the available Cards, Databases, Organizations, Phases, and Pipes options. Then configure your update frequency from 5-minute intervals to daily schedules.

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Send data from Pipefy to other destinations

Pipefy > Looker Studio

Pipefy > Power BI

Other visualizations

Pipefy > Amazon S3

Pipefy > BigQuery

Pipefy > Excel

Pipefy > Google Sheets

Pipefy > MySQL

Pipefy > PostgreSQL

Pipefy > Redshift

Pipefy > SQL Server

Choose a tool to visualize your Pipefy data

If the software you need is not listed, drop us a messagem. You can use almost every tool

Pipefy > Airtable

Pipefy > Alteryx

Pipefy > Amazon Quicksight

Pipefy > BIMachine

Pipefy > Cortex

Pipefy > Data Studio

Pipefy > Geckoboard

Pipefy > Grafana

Pipefy > IBM Cognos Analytics

Pipefy > Klipfolio

Pipefy > Looker Studio

Pipefy > Looker

Pipefy > Looqbox

Pipefy > Metabase

Pipefy > Microstrategy

Pipefy > Pentaho

Pipefy > Power BI

Pipefy > Qlik Cloud Analytics

Pipefy > Qlik Sense

Pipefy > Qlik

Pipefy > QlikView

Pipefy > Redash

Pipefy > Superset

Pipefy > Tableau

Pipefy > BI TOTVS

Pipefy > Zoho Analytics

Frequently Asked Questions (FAQ)

Answers about sending Pipefy data to Amazon S3 automatically

How do I send Pipefy card data to Amazon S3 automatically? ▼

Connect your Pipefy account to Kondado and select the Cards pipeline along with any other datasets you need. Configure Amazon S3 as your destination and set your preferred update frequency, and Kondado will handle the automated replication of card information including IDs, titles, and completion status directly to your specified S3 bucket.

What file format does Kondado use when saving Pipefy data to Amazon S3? ▼

Kondado stores your Pipefy data in optimized file formats compatible with Amazon Athena, Presto, and Dremio for immediate querying capabilities. This structure allows you to run SQL queries against your workflow data without additional transformation steps, making it ready for analysis as soon as it lands in your data lake.

Can I combine Pipefy workflow data with Salesforce or other sources in Amazon S3? ▼

Yes, Amazon S3 serves as a central repository where you can store Pipefy data alongside information from CRM systems, databases, or other platforms. Once consolidated, you can create unified datasets that connect process management metrics with sales performance or financial data for comprehensive business intelligence.

How frequently can I schedule Pipefy data updates to Amazon S3? ▼

Kondado offers configurable scheduling options ranging from every 5 minutes to daily intervals, allowing you to balance data freshness with processing costs. You can adjust these frequencies per pipeline, ensuring critical workflow data updates more frequently while maintaining hourly or daily schedules for less time-sensitive information.

Do I need technical skills to replicate Pipefy Organizations and Phases data to S3? ▼

No coding is required to set up the connection between Pipefy and Amazon S3 through Kondado's interface. The platform provides a guided setup process where you authenticate your Pipefy account, select the Organizations and Phases pipelines, and configure your S3 destination without writing API scripts or managing infrastructure.

What can I do with Pipefy data once it is stored in Amazon S3? ▼

You can query your Pipefy data using SQL through Amazon Athena or connect it to visualization tools like Power BI and Looker Studio for dashboard creation. Many users also combine S3-stored Pipefy information with BigQuery or PostgreSQL databases to build comprehensive analytics environments that track workflow efficiency across their organization.

Can I send Pipefy data from Amazon S3 to Power BI or Google Sheets? ▼

While Kondado replicates data directly from Pipefy to Amazon S3, you can subsequently connect your S3 bucket to Power BI or Google Sheets for reporting and analysis. This architecture allows you to maintain a single source of truth in S3 while distributing insights to stakeholders through their preferred visualization platforms.

Try out all the features for free for 14 days

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Try out all the features for free for 14 days