How does Kondado handle CSV files with different column counts from my FTP server?

The CSV pipeline normalizes variable structures by capturing row_number and column_number fields for every cell, allowing you to store files with differing schemas in a single MySQL dataset. This enables analysis of evolving log formats or monthly reports where headers change without breaking your downstream queries.

What specific data fields are available when replicating FTP files to MySQL?

Each record includes the cell value plus metadata fields: row_number, column_number, and __file_basename. These fields let you reconstruct original file layouts, filter by specific source files, and track data lineage within your MySQL queries.

How often can I schedule FTP to MySQL updates?

Kondado offers configurable schedules ranging from every 5 minutes to daily, hourly, or custom intervals. This flexibility supports near-real-time monitoring for operational logs or daily batch processing for bulk reporting datasets.

Can I combine FTP data in MySQL with other data sources?

Yes, once your FTP data resides in MySQL, you can join it with data replicated from FTP , BigQuery , or other sources. Create unified views that correlate file-based logs with transactional database records or Google Sheets reference data.

What file formats does the FTP to MySQL pipeline support?

Currently, the pipeline processes CSV files stored on your FTP server. The system automatically parses delimiters and extracts cell-level data with positional metadata, making flat file contents queryable through standard MySQL SQL syntax.

How does Kondado identify which FTP file each row came from?

The __file_basename field captures the original filename for every extracted row, enabling you to segment analysis by upload date, client, or file version. This metadata persists in MySQL, allowing you to filter reports by specific file batches or track data freshness by source filename.

Can I filter which files get replicated from my FTP server to MySQL?

Yes, during setup you specify file patterns or directories to monitor, ensuring only relevant CSVs enter your pipeline. This selective replication prevents unnecessary storage consumption in MySQL and focuses processing on operational files rather than entire server contents.

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Replicate FTP Files to MySQL Database Automatically

Sending FTP data to MySQL requires no coding when you use Kondado’s direct integration. Simply authenticate your FTP server as a data source, select which files to replicate, and configure your update schedule. The platform automatically extracts CSV files, detects schemas, and loads structured data into your MySQL database where it becomes immediately queryable. You can then analyze file contents with SQL, join FTP datasets with other business data, and power operational reports without manual file handling or complex import scripts.

Kondado automates FTP to MySQL replication by extracting CSV files from your server, normalizing variable column structures using fields like row_number and column_number, and loading them into your database on a configurable schedule ranging from every 5 minutes to daily. Once configured, your MySQL database stays current with automated updates, enabling consistent reporting across teams and eliminating delays between file uploads and analysis availability.

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The CSV pipeline captures every row and column from your FTP files, including metadata fields like __file_basename that track which source file each record originated from. This structure enables you to analyze log files with varying schemas, consolidate monthly sales reports stored as separate CSVs, or monitor server data dumps where column counts fluctuate between uploads. In MySQL, you can aggregate these normalized records, join them with transactional data from your ERP, or feed cleaned datasets into Power BI and Looker Studio for comprehensive visualization and business intelligence.

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FTP data available for MySQL

available pipeline

extractable fields

Available integrations

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

CSV

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

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How to send FTP data to MySQL

Sync data automatically — no code, no manual exports.

Connect Your FTP Server

Authenticate your FTP data source by entering server credentials and specifying the directory path where your CSV files reside.

Configure MySQL Destination

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

Select CSV Pipeline and Schedule

Choose the CSV pipeline to extract file contents with row-level metadata, then set your preferred update frequency from 5-minute intervals to daily batches.

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