No-code pipeline · Amazon S3 → PostgreSQL

Send data from Amazon S3 to PostgreSQL

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

Kondado provides a direct integration between Amazon S3 and PostgreSQL, automatically replicating CSV files from your S3 buckets to your PostgreSQL database on schedules ranging from every 5 minutes to daily, with configurable options for file reading patterns and data organization.

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Send Amazon S3 Data to PostgreSQL Automatically

To send Amazon S3 data to PostgreSQL, start by connecting your S3 bucket as a data source in Kondado, then configure your PostgreSQL database as the destination. Select the CSV Files pipeline to define how Kondado reads your stored files, including settings for delimiters and file prefixes. Once configured, Kondado replicates your S3 data to PostgreSQL on a configurable schedule, keeping your analytics database current without manual file transfers.

After replication, your S3 data becomes structured tables in PostgreSQL, ready for complex SQL analysis, joins with other business data, or feeding into visualization tools. This automated pipeline eliminates the need to manually download, transform, and upload files, letting analysts focus on extracting insights rather than data preparation.

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The CSV Files pipeline transforms raw storage into actionable database records, pulling files based on your specified prefixes and parsing them using custom delimiters to match your schema. Once in PostgreSQL, you can combine S3-stored customer behavior logs with transactional data from other sources, build custom dashboards in Looker Studio or Power BI, or create automated reports that refresh as new files land in your bucket. This seamless flow turns static file storage into a dynamic analytics environment where every CSV upload triggers updated metrics and fresh business intelligence.

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Replicated to PostgreSQL

Dynamic data

Kondado automatically reads the schema of your Amazon S3. All tables, views, and fields available in your account are extracted without manual configuration.

available pipeline

PostgreSQL

Destination

What Kondado extracts

CSV Files

Includes fields such as Start reading date, Column delimiter, and File prefix, enabling efficient data reading and organization.

See all available data → Send Amazon S3 to PostgreSQL →

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How to send Amazon S3 data to PostgreSQL

Sync data automatically — no code, no manual exports.

Connect your Amazon S3 bucket

Add Amazon S3 as a data source in Kondado by providing your bucket credentials and region details to establish the initial connection.

Configure PostgreSQL destination

Set up PostgreSQL as your destination by entering your database connection details, including host, port, and authentication credentials.

Select CSV pipeline and schedule

Choose the CSV Files pipeline, define your file reading parameters such as prefixes and delimiters, then set your preferred update frequency from 5-minute intervals to daily.

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Choose a tool to visualize your Amazon S3 data

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

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Frequently Asked Questions (FAQ)

Answers about sending Amazon S3 data to PostgreSQL automatically

How does Kondado replicate CSV files from Amazon S3 to PostgreSQL? ▼

Kondado connects directly to your S3 bucket using the CSV Files pipeline, reading files based on prefixes and date patterns you configure. The platform parses each file using your specified column delimiter and loads the structured data into PostgreSQL tables. This process runs automatically on your chosen schedule, checking for new files and appending or updating records accordingly.

What file formats can I replicate from S3 to PostgreSQL using Kondado? ▼

Currently, Kondado supports CSV Files pipelines for S3 to PostgreSQL replication, enabling you to process comma-separated values and other delimited text formats. You can configure the column delimiter, file prefixes, and start reading dates to handle various CSV structures. For other formats, you may need to convert files to CSV before storage in S3.

How often does Kondado update PostgreSQL with new S3 data? ▼

Kondado checks your S3 bucket for new files on a configurable schedule that you set, with options ranging from every 5 minutes to daily intervals. When new files matching your criteria appear, the platform automatically replicates them to PostgreSQL without requiring manual intervention. This ensures your database stays current with your storage while balancing processing frequency against your analytics needs.

Can I combine Amazon S3 data with other sources in the same PostgreSQL database? ▼

Yes, Kondado can replicate data from multiple sources into the same PostgreSQL destination, allowing you to join S3 CSV data with information from BigQuery, Google Sheets, or other databases. This creates a unified analytics environment where file-based storage and application data coexist in structured tables. Analysts can then run cross-source SQL queries to correlate events, transactions, and behavioral data.

How is data structured when Amazon S3 files arrive in PostgreSQL? ▼

Each CSV file becomes a structured table in PostgreSQL with columns matching the headers or positions defined in your file configuration. Kondado preserves the data types and relationships specified during pipeline setup, creating a relational structure that supports indexing, joins, and complex queries. This transformation turns flat files into query-ready database records that work seamlessly with Power BI and other BI tools.

What happens to my PostgreSQL data when I add new columns to S3 CSV files? ▼

When you modify the structure of your CSV files in S3, you can update the pipeline configuration in Kondado to recognize new columns and adjust the PostgreSQL schema accordingly. The platform allows you to remap fields and handle schema evolution without breaking existing data flows. This flexibility ensures your PostgreSQL tables can grow with your reporting requirements as your data sources evolve.

Can I filter which S3 files get replicated to PostgreSQL? ▼

Yes, the CSV Files pipeline includes configuration options for file prefixes and start reading dates, letting you target specific folders or file naming patterns within your bucket. You can set these filters to process only relevant datasets, such as daily exports or specific department files, while ignoring temporary or archived data. This selective replication keeps your PostgreSQL database focused on actionable information.

How do I visualize data after replicating from S3 to PostgreSQL? ▼

Once your S3 data resides in PostgreSQL, you can connect the database to visualization platforms like Looker Studio or Power BI to build custom dashboards and reports. The structured SQL tables support complex aggregations and joins that power interactive charts and automated reporting. Since Kondado updates PostgreSQL on your configured schedule, these visualizations reflect the latest file uploads without manual refresh.

Try out all the features for free for 14 days

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