Sync data from Snowflake Iceberg to S3
Connect your data from Snowflake Iceberg to S3 with Hightouch. No APIs, no months-long implementations, and no CSV files. Just your data synced forever.
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Use cases
Sync data from Snowflake Iceberg to S3
- Export user data and product data to CSVs, with or without headers
- Customize field names and S3 object paths via Hightouch
What methods can I use to model my Snowflake Iceberg data?
SQL editor
Create and Edit SQL from your browser. Hightouch supports SQL native to Snowflake Iceberg.
Table selector
Select available tables and sheets from Snowflake Iceberg and sync using existing views without having to write SQL.
Customer Studio
For less technical users, pass traits and audiences from Snowflake Iceberg using our visual segmentation builder.
FAQs
There are several options to sync data between sources. You can manually build and maintain a data pipeline, use a point-to-point solution such as Zapier, or you can manually upload CSVs.
With Hightouch, you get:
- Automation: You do not need to build and maintain custom data pipelines and you do not have to have your team do manual work
- Simplicity: You avoid a complex web of integrations caused by point-to-point solutions by syncing data from your source
- Speed: You can get set up in quickly - the average Hightouch customer starts syncing data in 23 minutes
- Control: companies of all sizes have access to enterprise-level controls including observability, dbt integrations, and version control
- Security: Hightouch never stores your data and is HIPAA, GDPR, CCPA, and SOC-2 compliant
90% of all Hightouch syncs complete in 30 seconds or less, and the platform enables non-technical users to self-serve.
With Hightouch, you can sync data as frequently as it changes within your Snowflake Iceberg. You can trigger data syncs manually or schedule them to run at an interval or custom recurrence as often as once per minute.
Hightouch offers a basic mapper or advanced mapper that allows you to visually match columns from your Snowflake Iceberg to fields in S3.
Snowflake is a managed cloud data warehouse that helps you consolidate and aggregate your data into a single, centralized platform to tackle analytics use cases. These workloads include data warehousing, data lakes, data engineering, application development, data sharing, and business intelligence.
Amazon Simple Storage Service (Amazon S3) is storage for the Internet. It's highly scalable, reliable, fast, and inexpensive.
Yes, if you integerate Snowflake Iceberg and S3 using Hightouch, in-warehouse planning is supported.
Great, but what is in-warehouse planning?
Between every sync, Hightouch notices any and all changes in your data model. This allows you to only send updated results to your destination (in this case S3). With the baseline setup, Hightouch picks out only the rows that need to be synced by querying every row in your data model before diffing using Hightouch’s infrastructure.
The issue here is this can be slow for large models.
Warehouse Planning allows Hightouch to do this diff directly in your warehouse. Read more on how this works here.