Connect HubSpot to Amazon S3 — Raw Data Lake Storage

Log into the Supermetrics Hub, create a new data transfer, select HubSpot as the source and Amazon S3 as the destination. Provide your S3 bucket name, region, and AWS credentials (access key + secret key or IAM role ARN). Choose your metrics, set a schedule, and start the transfer. Supermetrics writes structured files directly to your S3 bucket — no custom scripts needed. For optimal downstream analytics, choose Parquet format: it's columnar, compressed, and works natively with Athena, Redshift Spectrum, and AWS Glue crawlers without schema definition.

Supermetrics is SOC 2 Type II certified and GDPR compliant. Data transfers are encrypted in transit via TLS. Once in S3, your data inherits AWS-native security controls: server-side encryption (SSE-S3, SSE-KMS, or SSE-C), S3 bucket policies to restrict access by IAM principal or IP range, S3 Object Lock for immutable audit trails, and optional VPC endpoints so traffic never leaves the AWS backbone. You can also enable S3 Access Logging and CloudTrail data events to track every read and write to your marketing data. Supermetrics does not retain your data after delivery.

Absolutely. S3 is the standard landing zone for AWS data lakes. Transfer HubSpot alongside Google Ads, GA4, CRM exports, and any other data into the same bucket, then query across all sources with Amazon Athena using standard SQL — no loading step required. For automated processing, configure S3 Event Notifications to trigger a Lambda function whenever Supermetrics delivers a new file, or run an AWS Glue crawler to update your Data Catalog automatically. Supermetrics supports 170+ sources, all deliverable to the same S3 prefix structure for a clean, partitioned data lake.

All standard HubSpot reporting metrics and dimensions are available, including Contacts created, Deals created, Deal amount, Deal close rate, Closed won deals, Amount won, and many more. You choose exactly which fields to include during transfer setup. Data arrives as clean, structured files in CSV, JSON, or Parquet format. Parquet is especially powerful for S3-based analytics: Athena and Redshift Spectrum can push predicate filters down to the file level, meaning queries scan only the columns and row groups they need — dramatically reducing both query time and per-query cost.

You can schedule transfers hourly, daily, weekly, or monthly. Most teams use daily transfers for a reliable morning-ready dataset. Supermetrics handles incremental delivery so only new and updated records are written, keeping your S3 costs low and file sizes manageable. For real-time reaction workflows, pair your daily Supermetrics delivery with an S3 Event Notification that triggers a Lambda function — for example, to recalculate budget pacing or fire an alert the moment fresh HubSpot data lands in your bucket.

Yes. Supermetrics pulls deal data including stage, amount, close rate, and pipeline. Historical snapshots let you track pipeline changes over time.

Yes. Open rates, click rates, bounce rates, and form submissions are all available as structured files in S3.