No-code pipeline · monday.com → Amazon S3

Send data from monday.com to Amazon S3

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From monday.com to Amazon S3: managed, scheduled, no code.

Creating a pipeline that sends data from monday.com to Amazon S3 data lakes takes only a few minutes with Kondado. And the whole integration from monday.com to Amazon S3 is managed and executed by our platform. With Kondado, you can focus on extracting value from monday.com data and combining it with other data in your Amazon S3 data lake

Connect monday.com now →

Send monday.com Data to Amazon S3 Automatically

How to send monday.com data to Amazon S3? Start by connecting your monday.com account as a data source, then select Amazon S3 as your destination. Kondado handles the replication automatically, delivering your project management data to your S3 buckets on a configurable schedule without requiring any coding or manual exports. Once your data arrives in S3, you can query it directly with Amazon Athena, connect it to BigQuery for cross-platform analysis, or feed it into business intelligence tools like Power BI and Looker Studio for comprehensive project analytics and custom dashboard creation.

Kondado provides a direct integration between monday.com and Amazon S3, replicating data from five available pipelines including Board Items, Activity Logs, and Users. The platform delivers 142 fields of project management data to your S3 storage on a configurable schedule ranging from every 5 minutes to daily, enabling automated data lakes for analytics workflows.

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Replicate your monday.com Board Items and Activity Logs pipelines to Amazon S3 for comprehensive project tracking and historical analysis. With Board Items data in S3, analysts can build custom attribution models tracking task completion rates across workspaces, while Activity Logs enable compliance auditing and workflow optimization by preserving complete event histories. Combine these with the Users pipeline to correlate task assignments with team productivity metrics, creating a unified data lake that supports advanced SQL queries in Athena or integration with PostgreSQL warehouses for enterprise reporting.

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Replicated to Amazon S3

monday.com data available for Amazon S3

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

available pipelines

142

extractable fields

Amazon S3

Destination

Available integrations

Board Settings

Includes fields such as board_id, group_id, and workspace_id, allowing management of specific settings for each board.

Board Items

Contains information such as id, name, and updated_at, essential for tracking and managing items within each board.

Items: Conversations (Updates)

Presents fields such as id, item_id, and created_at, allowing tracking of updates and interactions related to each item.

Activity Logs

Records events with fields such as id, created_at, and event, providing a detailed history of activities performed.

Users

Includes fields such as user_id and creator_name, allowing identification and management of users interacting with items and updates.

See all available data → Send monday.com to Amazon S3 →

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How to send monday.com data to Amazon S3

Sync data automatically — no code, no manual exports.

Connect monday.com data source

Authenticate your monday.com account in Kondado with one click using OAuth credentials, granting access to your boards and workspace data without technical configuration.

Configure Amazon S3 destination

Enter your AWS credentials and specify the target S3 bucket and folder path where Kondado will deliver your monday.com data files, with optional partitioning settings for organized storage.

Select pipelines and schedule

Choose from the five available pipelines such as Board Items and Activity Logs, then set your preferred replication frequency from every 5 minutes to daily for automated data delivery.

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Send data from monday.com to other destinations

monday.com > Looker Studio

monday.com > Power BI

Other visualizations

monday.com > Amazon S3

monday.com > BigQuery

monday.com > Excel

monday.com > Google Sheets

monday.com > MySQL

monday.com > PostgreSQL

monday.com > Redshift

monday.com > SQL Server

Choose a tool to visualize your monday.com data

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

monday.com > Airtable

monday.com > Alteryx

monday.com > Amazon Quicksight

monday.com > BIMachine

monday.com > Cortex

monday.com > Data Studio

monday.com > Geckoboard

monday.com > Grafana

monday.com > IBM Cognos Analytics

monday.com > Klipfolio

monday.com > Looker Studio

monday.com > Looker

monday.com > Looqbox

monday.com > Metabase

monday.com > Microstrategy

monday.com > Pentaho

monday.com > Power BI

monday.com > Qlik Cloud Analytics

monday.com > Qlik Sense

monday.com > Qlik

monday.com > QlikView

monday.com > Redash

monday.com > Superset

monday.com > Tableau

monday.com > BI TOTVS

monday.com > Zoho Analytics

Frequently Asked Questions (FAQ)

Answers about sending monday.com data to Amazon S3 automatically

How does Kondado replicate monday.com data to Amazon S3 without coding? ▼

Kondado connects directly to your monday.com account using OAuth authentication, then automatically extracts data from your selected pipelines and loads it into your specified S3 bucket. The platform handles schema mapping and file formatting automatically, delivering structured data files ready for immediate analysis in your data lake.

What monday.com data fields are available in the Board Items pipeline? ▼

The Board Items pipeline includes essential fields such as item ID, name, updated timestamps, and board associations, totaling 142 available fields across all pipelines. This data enables detailed tracking of task progress, priorities, and status changes within your project management workflows stored in S3.

Can I schedule monday.com data updates to Amazon S3 every 15 minutes? ▼

Yes, Kondado supports configurable replication schedules ranging from every 5 minutes to daily intervals, allowing you to balance data freshness with API rate limits and storage costs. You can adjust these frequencies per pipeline based on your specific analytics requirements and data latency needs.

In what file format does monday.com data arrive in Amazon S3? ▼

Kondado delivers monday.com data to S3 in optimized columnar formats such as Parquet or compressed CSV, depending on your configuration, enabling efficient querying through Amazon Athena or Spark. These formats support partitioning by date or board ID, improving query performance for large project datasets.

Can I combine monday.com data in S3 with other sources like Google Sheets or PostgreSQL? ▼

Absolutely, you can replicate data from monday.com alongside other sources into S3, then join these datasets using Athena or load them into BigQuery and PostgreSQL. This enables unified reporting across project management, CRM, and financial data for comprehensive business intelligence.

How do I query monday.com Activity Logs stored in Amazon S3? ▼

Once Activity Logs data lands in your S3 bucket, you can query it directly using Amazon Athena with standard SQL, or connect the data to Power BI and Looker Studio for visual analysis. The structured format preserves event timestamps, user actions, and board changes, supporting compliance audits and workflow efficiency studies.

Can I send monday.com data to Amazon S3 and Google BigQuery simultaneously? ▼

Yes, Kondado supports multiple destinations for the same data source, allowing you to replicate monday.com data to both Amazon S3 and BigQuery concurrently. This flexibility lets you maintain a raw data archive in S3 while performing transformations in BigQuery, or serve different analytics teams with their preferred storage solutions.

Try out all the features for free for 14 days

Related on Kondado

Try out all the features for free for 14 days