Connect Apify and S3 so every scraping run archives its data directly to cloud storage without manual file transfers.
Every Apify actor run saves timestamped results to your S3 bucket automatically.
Drop a URL list into S3 and Neotask launches the matching Apify actor immediately.
Versioned S3 objects preserve every scraping run so past datasets are always retrievable.
Run any Apify actor on a schedule and save each dataset as a timestamped JSON or CSV file in S3.
When a new URL list lands in S3, Neotask detects the upload and starts the correct Apify actor automatically.
Convert Apify actor output to JSON, CSV, or NDJSON and route each format to a dedicated S3 prefix.
Monitor target URLs with Apify and push change-detection diffs as new S3 objects for downstream consumers.
After each Apify run completes and uploads to S3, trigger a summary notification to your team channel.
Link your Apify API token and S3 credentials to Neotask in one setup flow.
Tell Neotask which Apify actor maps to which S3 bucket and prefix, and set your preferred output format.
Neotask executes actors on schedule or on S3 upload events, then saves results as versioned objects.
| Capability | Apify | S3 |
|---|---|---|
| Run scraping actors | Yes | No |
| Store datasets as files | No | Yes |
| Schedule recurring jobs | Yes | No |
| Lifecycle and retention rules | No | Yes |
| Structured data extraction | Yes | No |
| Versioned object storage | No | Yes |
Apify runs web scraping actors that extract structured data from any website at scale. S3 provides durable, low-cost object storage that retains any volume of files indefinitely. Connecting them through Neotask removes every manual step between data extraction and storage.
Data pipelines break down at handoff points. When a developer has to download Apify results and upload them to S3 by hand, runs get skipped, files get renamed inconsistently, and historical records go missing. Neotask automates the entire handoff so each actor run produces a predictably named, immediately accessible S3 object.
Timestamped object keys mean you accumulate a full historical archive by default. Retention rules in S3 handle cleanup. You query any past run by date without rebuilding it.
The integration works in both directions. Apify results flow out to S3 after every run. Input files stored in S3 flow in to trigger new Apify runs. A URL list dropped into an input prefix starts the correct actor within seconds, turning S3 into a lightweight job queue.
Whether you run one actor or fifty, the routing logic stays the same. Each actor maps to a bucket prefix, each run creates one object, and Neotask handles the mapping. There is no custom Lambda, no cron script, and no fragile bash pipeline to maintain.
Teams using this integration reduce data pipeline maintenance time and gain confidence that every scraping run is captured and accessible for downstream analysis.
Use a date-stamped key pattern like actor-name/YYYY-MM-DD/run-id.json so S3 objects sort chronologically without extra tooling.
Set an S3 lifecycle rule on your archive prefix to transition objects to Glacier after 90 days and cut long-term storage costs.
Map a separate S3 prefix per Apify actor so downstream consumers can subscribe to exactly the data feed they need.
Neotask supports JSON, CSV, and NDJSON. You choose the format per actor when configuring the integration.
Yes. You can configure Neotask to fan out a single S3 upload event to several actors running in parallel.
No by default. Neotask creates a new timestamped object per run, preserving full history unless you explicitly configure overwrite mode.
Neotask works with AWS S3 and any S3-compatible endpoint, including Cloudflare R2 and MinIO.
Stop manually moving scraped data into storage. Let Neotask automate the entire pipeline from extraction to archive.
$0/mo
Download without a card and start for free.
$50/mo
The full personal agent platform for one person.
$100/mo
One company workspace with room to add your team.
$200/mo
Multiple workspaces and capacity for larger teams.
Explore: Integrations · Skills · Glossary · Solutions · Use cases · Examples · Comparisons · Templates · Blog · Docs