No-code pipeline · FTP → Amazon S3

Send data from FTP to Amazon S3

Get started for free

No credit card required | 14 days | 10 million records | 30 pipelines

or sign up with your email

By signing up, you agree to Kondado’s Terms of service and Privacy policy

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

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

Connect FTP now →

Replicate FTP Data to Amazon S3 Automatically

Connecting your FTP server to Amazon S3 requires a reliable data pipeline that automates file transfers without manual intervention. Kondado provides a direct integration between your FTP data source and Amazon S3, enabling automated replication of CSV files on a configurable schedule. Simply authenticate your FTP credentials, specify your S3 bucket as the destination, and define how frequently you want files transferred, whether every 5 minutes, hourly, or daily. Once configured, your FTP files land in S3 ready for analysis with Athena, Presto, or Dremio, supporting your data virtualization layer without additional engineering work. This automated workflow ensures your file-based data feeds directly into scalable storage where it can power business intelligence and analytics workflows.

Kondado replicates FTP files to Amazon S3 on a configurable schedule, parsing CSV data with support for varying column structures through metadata fields including row_number, column_number, and __file_basename, enabling analysis of dynamic file formats directly within your data lake architecture.

Our prices start from $19 USD/month, and you can try Kondado for free for 14 days with no credit card required

Available Pipelines

The CSV pipeline extracts structured data from your FTP files while preserving critical metadata through fields like row_number, column_number, and __file_basename. This enables sophisticated analysis of files with inconsistent schemas or varying column counts, ensuring your data lake accommodates dynamic formats without preprocessing. With your FTP data now stored in Amazon S3, you can combine these file-based datasets with information from additional business sources, creating unified analytics environments in BigQuery, PostgreSQL, or Power BI for comprehensive business intelligence.

Try out all the features for free for 14 days

Replicated to Amazon S3

FTP data available for Amazon S3

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

available pipeline

extractable fields

Amazon S3

Destination

Available integrations

CSV

Table includes fields such as row_number, column_number, and __file_basename, enabling analysis of data from files with varying columns.

See all available data → Send FTP to Amazon S3 →

Try out all the features for free for 14 days

How to send FTP data to Amazon S3

Sync data automatically — no code, no manual exports.

Connect Your FTP Data Source

Enter your FTP server credentials including host, port, username, and password in Kondado's interface to establish the initial connection. Verify the connection to ensure Kondado can access your file directories and read CSV files from your FTP server.

Configure Amazon S3 Destination

Specify your target S3 bucket name and desired folder path where replicated files should land, ensuring proper AWS permissions are in place. This setup enables seamless data flow from your FTP server into Amazon S3's scalable storage environment.

Select Data and Set Schedule

Choose the CSV pipeline to extract your file data and configure your update frequency, selecting intervals from 5 minutes to daily based on your business requirements. This final step activates automated replication, ensuring your FTP files populate Amazon S3 on your preferred timeline.

Try out all the features for free for 14 days

Hundreds of data-driven companies trust Kondado

Why Kondado?

Focus on extracting value from your data and leave the rest to us

Wherever you need

With the same platform, you send data to AI (Claude/ChatGPT via MCP), reports, spreadsheets, databases, data warehouses, and data lakes. ETL and ELT

Learn More About Our Platform →

From wherever you need

Data from over 80 sources for Marketing, Ecommerce, ERPs, Customer Service, Finance, Databases, and much more

Learn More About Our Data Sources →

Predictable pricing

No surprise invoices, pick a plan and change it anytime

Check out our plans →

Send data from FTP to other destinations

FTP > Looker Studio

FTP > Power BI

Other visualizations

FTP > Amazon S3

FTP > BigQuery

FTP > Excel

FTP > Google Sheets

FTP > MySQL

FTP > PostgreSQL

FTP > Redshift

FTP > SQL Server

Choose a tool to visualize your FTP data

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

FTP > Airtable

FTP > Alteryx

FTP > Amazon Quicksight

FTP > BIMachine

FTP > Cortex

FTP > Data Studio

FTP > Geckoboard

FTP > Grafana

FTP > IBM Cognos Analytics

FTP > Klipfolio

FTP > Looker Studio

FTP > Looker

FTP > Looqbox

FTP > Metabase

FTP > Microstrategy

FTP > Pentaho

FTP > Power BI

FTP > Qlik Cloud Analytics

FTP > Qlik Sense

FTP > Qlik

FTP > QlikView

FTP > Redash

FTP > Superset

FTP > Tableau

FTP > BI TOTVS

FTP > Zoho Analytics

Frequently Asked Questions (FAQ)

Answers about sending FTP data to Amazon S3 automatically

How does Kondado handle CSV files with different column structures when replicating from FTP to Amazon S3? ▼

The CSV pipeline includes metadata fields like row_number, column_number, and __file_basename that track positional data and source filenames. This allows you to analyze files with varying column counts within the same dataset, accommodating dynamic schemas without requiring manual standardization before replication.

What metadata fields are added to my data when replicating FTP files to Amazon S3? ▼

Kondado appends fields including row_number, column_number, and __file_basename to every record extracted from your FTP CSV files. These fields enable precise tracking of data origin and structure, supporting advanced analytics even when source files contain inconsistent formatting or irregular column arrangements.

How frequently can I schedule updates when sending FTP data to Amazon S3? ▼

Kondado offers flexible scheduling options ranging from every 5 minutes to daily intervals, allowing you to balance data freshness with processing efficiency. Configure your update frequency based on how often your FTP files change, ensuring your Amazon S3 bucket reflects the latest information without unnecessary processing overhead.

Can I combine FTP data stored in Amazon S3 with other business sources for unified reporting? ▼

Yes, once your FTP data resides in Amazon S3, you can blend it with datasets from FTP and other platforms. Send the combined information to BigQuery, PostgreSQL, or Power BI to create comprehensive reports that unite file-based data with transactional records and application metrics.

What analytics tools work best with FTP data stored in Amazon S3? ▼

Amazon S3 integrates seamlessly with Athena, Presto, and Dremio for data virtualization, enabling SQL-based analysis of your replicated FTP files without moving data. You can also pipe information to Looker Studio, Power BI, or BigQuery to build custom dashboards and reports that visualize trends across your file-based datasets.

How do I set up automated replication from multiple FTP directories to different S3 buckets? ▼

Configure separate pipelines for each FTP directory you want to monitor, specifying distinct S3 bucket destinations or folder paths for each data stream. Kondado allows you to manage multiple FTP-to-S3 workflows simultaneously, ensuring organized data separation while maintaining automated updates across all your file transfer requirements.

Try out all the features for free for 14 days

Related on Kondado

Try out all the features for free for 14 days