No-code pipeline · Google Cloud Storage → Redshift

Send data from Google Cloud Storage to Redshift

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From Google Cloud Storage to Redshift: managed, scheduled, no code.

Kondado replicates your Google Cloud Storage CSV files to Amazon Redshift on a configurable schedule, automatically tracking file metadata including paths, basenames, and insertion timestamps so your data warehouse stays current without manual uploads.

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Send Google Cloud Storage Data to Redshift Automatically

Connecting Google Cloud Storage to Redshift requires no coding when you use Kondado. Simply authenticate your Google Cloud Storage account, configure your Redshift cluster as the destination, and select which CSV file metadata you want to replicate. Kondado handles the automated data transfer on your chosen schedule, whether you need updates every 5 minutes or daily batches, ensuring your data warehouse reflects the latest file information without manual intervention.

Once your data arrives in Redshift, you can query file information using standard SQL alongside your existing datasets. This enables comprehensive analytics workflows that combine object storage metadata with transactional data for deeper operational insights.

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Available Data Pipelines

The CSV pipeline captures essential file metadata including __file_basename, __file_path, and __kdd_insert_time fields, giving you complete visibility into your storage objects. In Redshift, you can analyze file arrival patterns to optimize data ingestion workflows or build monitoring dashboards that track storage utilization across different buckets and prefixes.

Combine this object metadata with sales data, application logs, or marketing analytics already in your Redshift warehouse to create unified reports. For example, correlate CSV upload timestamps from Google Cloud Storage with conversion events to measure data pipeline latency impacts on business decisions, or use file path analysis to automate quality checks on incoming datasets before they reach production tables.

FAQ

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Replicated to Redshift

Google Cloud Storage data available for Redshift

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

available pipeline

extractable fields

Redshift

Destination

Available integrations

CSV

Table includes information about CSV files, featuring fields such as __file_basename, __file_path, and __kdd_insert_time, enabling tracking of the modification date and value of each file.

See all available data → Send Google Cloud Storage to Redshift →

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How to send Google Cloud Storage data to Redshift

Sync data automatically — no code, no manual exports.

Connect Google Cloud Storage

Authenticate your Google Cloud Storage account in Kondado by providing your bucket details and access credentials to establish the data source connection.

Configure Redshift destination

Enter your Amazon Redshift cluster connection details including host, database name, and credentials to specify where your CSV file metadata should be replicated.

Select CSV pipeline and schedule

Choose the CSV pipeline to track your file metadata and set your preferred update frequency, from every 5 minutes to daily, to keep your Redshift warehouse synchronized with Google Cloud Storage activity.

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Send data from Google Cloud Storage to other destinations

Google Cloud Storage > Looker Studio

Google Cloud Storage > Power BI

Other visualizations

Google Cloud Storage > Amazon S3

Google Cloud Storage > BigQuery

Google Cloud Storage > Excel

Google Cloud Storage > Google Sheets

Google Cloud Storage > MySQL

Google Cloud Storage > PostgreSQL

Google Cloud Storage > Redshift

Google Cloud Storage > SQL Server

Choose a tool to visualize your Google Cloud Storage data

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

Google Cloud Storage > Airtable

Google Cloud Storage > Alteryx

Google Cloud Storage > Amazon Quicksight

Google Cloud Storage > BIMachine

Google Cloud Storage > Cortex

Google Cloud Storage > Data Studio

Google Cloud Storage > Geckoboard

Google Cloud Storage > Grafana

Google Cloud Storage > IBM Cognos Analytics

Google Cloud Storage > Klipfolio

Google Cloud Storage > Looker Studio

Google Cloud Storage > Looker

Google Cloud Storage > Looqbox

Google Cloud Storage > Metabase

Google Cloud Storage > Microstrategy

Google Cloud Storage > Pentaho

Google Cloud Storage > Power BI

Google Cloud Storage > Qlik Cloud Analytics

Google Cloud Storage > Qlik Sense

Google Cloud Storage > Qlik

Google Cloud Storage > QlikView

Google Cloud Storage > Redash

Google Cloud Storage > Superset

Google Cloud Storage > Tableau

Google Cloud Storage > BI TOTVS

Google Cloud Storage > Zoho Analytics

Frequently Asked Questions (FAQ)

Answers about sending Google Cloud Storage data to Redshift automatically

How does Kondado replicate data from Google Cloud Storage to Redshift? ▼

Kondado connects directly to your Google Cloud Storage buckets and automatically extracts CSV file metadata, then loads this information into your specified Redshift tables on your configured schedule. The pipeline tracks file paths, basenames, and timestamps without requiring you to write custom ETL scripts or manage file transfer infrastructure.

What specific data fields are available when replicating Google Cloud Storage to Redshift? ▼

The CSV pipeline includes eight fields such as __file_basename, __file_path, and __kdd_insert_time, enabling you to track file locations, names, and when they were processed. This metadata allows you to monitor file modifications, analyze storage structure, and maintain audit trails of object changes directly within Redshift.

How frequently can I update my Redshift data from Google Cloud Storage? ▼

Kondado offers configurable update schedules ranging from every 5 minutes to daily intervals, allowing you to balance data freshness with warehouse compute costs. You can adjust these frequencies based on your business needs, whether you require near-real-time file tracking or periodic batch updates for historical analysis.

Can I combine Google Cloud Storage data with other sources in my Redshift warehouse? ▼

Yes, once your file metadata resides in Redshift, you can join it with data from other pipelines such as PostgreSQL, application APIs, or database sources. This enables comprehensive analytics that correlate storage events with business transactions, user behaviors, or operational metrics stored in the same warehouse.

What can I build with Google Cloud Storage data in Redshift? ▼

You can create custom dashboards in Power BI or Looker Studio connected to Redshift that visualize file upload trends, storage growth patterns, and data pipeline health. Analysts also use this metadata to trigger downstream processing workflows, validate data completeness, and generate operational reports that combine object storage metrics with core business KPIs.

Does Kondado support other destinations besides Redshift for Google Cloud Storage data? ▼

Yes, you can send your Google Cloud Storage data to BigQuery, PostgreSQL, or Google Sheets using the same CSV pipeline configuration. This flexibility allows you to route file metadata to the analytics platform that best fits your team's workflow without reconfiguring your source connection.

How is the CSV file data structured when it arrives in Redshift? ▼

Each row in Redshift represents a single CSV file from your Google Cloud Storage bucket, with columns containing metadata attributes like file paths and processing timestamps rather than the file content itself. This structure enables efficient SQL queries that track file inventory, monitor upload patterns, and audit data lineage across your storage infrastructure.

Do I need to prepare my Redshift database before connecting Google Cloud Storage? ▼

You only need to provide your Redshift cluster credentials and specify the target database, as Kondado automatically creates the necessary schema and tables to store your CSV file metadata. The pipeline handles all table structure definitions based on the eight available fields, so you can start querying file information immediately after the first replication completes. ### HowTo

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