AWS S3 integration
Read and write files in Amazon S3 from your workflows — use a bucket as a data source, a destination, or a data lake for any pipeline.
What the AWS S3 integration does
Amazon S3 is where a huge amount of data lands — exports, backups, logs, and the raw files that feed pipelines. The OctaviaFlow AWS S3 integration lets your workflows read those files and write results back, turning a bucket into a first-class source or destination.
Read an object to drive a workflow, list a prefix to process many files, or write output back to S3 as the last step of a pipeline. Because S3 is a step in a larger flow, a file can feed a database, a warehouse, or an API — or collect the results for archival.
Connect with encrypted credentials scoped to the buckets you choose.
What you can do
Read & download files
Pull an object from S3 into a workflow — a CSV to parse, a JSON export to process, or any file to move onward.
Write & upload files
Write results back to S3 as the output of a workflow — a report, a transformed dataset, or an archived copy.
List and process many objects
Enumerate a prefix and loop over the files, processing each one and routing the results.
Feed pipelines and data lakes
Land data into S3 from databases and apps, or read raw files out of S3 for downstream loading and transformation.
Multi-step automations
Combine S3 with databases, warehouses, transforms, AI steps, and other connectors to model real file pipelines.
Secure credentials
Connect with access keys stored encrypted; the connector reads and writes only the buckets you configure.
How it works in AWS S3
- 1
Connect AWS S3
Add your access credentials and region in Connectors, scoped to the buckets you want to use.
- 2
Add an S3 step
Drop a read (download) or write (upload) action into your workflow, or list a prefix to process many files.
- 3
Route the data
Parse files you read, map fields for downstream writes, and send results wherever they need to go.
- 4
Run or schedule
Run on demand or on a schedule, and combine with other triggers to keep the bucket in sync.
Popular AWS S3 automations
Load S3 files into a warehouse
Read CSV or JSON exports from a bucket, transform them, and load the rows into Snowflake or a database.
Export data to S3
Write query results, reports, or backups to S3 on a schedule for archival or downstream systems.
Process incoming files
List a prefix of uploaded files, process each one, and route the results to the right destination.
Data-lake ingestion
Land raw data from databases and apps into an S3 data lake for later loading and analysis.
Move files between systems
Read from S3 and write to another store, or vice versa, as part of a larger workflow.
AI on document files
Read a file from S3, extract or summarize it with an AI step, and write the structured result onward.
AWS S3 integration FAQ
Can OctaviaFlow read files from and write files to S3?
Yes. Read actions download objects into a workflow and write actions upload results, so a bucket can be a source, a destination, or both.
Can it process many files at once?
Yes. List a prefix and loop over the objects, processing each file and routing its results.
What file formats are supported?
Any file. Structured formats like CSV and JSON can be parsed into records for downstream steps; other files can be moved as-is.
Which buckets can it access?
Only the buckets your credentials permit, and the ones you point a step at — reads and writes are scoped to what you configure.
Are my credentials secure?
Access keys are stored encrypted. See our privacy policy for details.
Automate AWS S3 with your whole stack
Connect AWS S3 in minutes and let OctaviaFlow deliver the right message at the right moment — powered by data from anywhere.