We’re excited to strengthen our partnership with Snowflake and take part in Snowflake’s GTM coaching program. As part of the program, we’ll work more closely with the Snowflake team to highlight joint customer use cases and help more organizations understand the value Skyvia and Snowflake can deliver together.
The Data Integration Challenge
Business data needed for reporting, analytics, and AI is rarely in one place. It is spread across CRM, marketing, finance, and support applications, as well as cloud and on-premises databases. Every new source adds integration work, from setting up data loads to maintaining connectors as APIs change.
The work continues once the data reaches Snowflake. New sources may need to fit an existing data model, while customer segments, payment status, and other modeled results need to reach operational applications. Managing those steps separately can mean more scripts, manual exports, and tools for the data team to maintain.
Why Skyvia and Snowflake Deliver More Value Together
Snowflake provides the central platform for analytics and AI, while Skyvia manages the data integration around it. With connectivity to 200+ sources, visual configuration, scheduling, and monitoring, Skyvia reduces the routine work involved in building and operating Snowflake pipelines.
For Skyvia customers, Snowflake is a natural next step when point-to-point integrations are no longer enough for their analytics needs. For Snowflake customers, Skyvia provides a managed way to connect more business systems and bring warehouse data back into daily workflows.
How Skyvia Works with Snowflake
Skyvia automates data loading from cloud applications and databases into Snowflake, using COPY INTO for bulk loads. Teams can then use Skyvia to run dbt Core transformations on their own Snowflake warehouse, turning raw data into datasets ready for reporting and analytics.
Reverse ETL sends modeled results back to CRM, marketing, and support applications, where teams can use them in their daily work. Skyvia Connect makes Snowflake data available to other applications through OData and SQL endpoints, and to AI agents through MCP endpoints.
What This Looks Like in Practice
Customers are already using Skyvia with Snowflake to reduce manual work and make business data available sooner.
CashMe previously spent five working days each week collecting data and preparing marketing KPIs. With Skyvia, the company automated data collection from multiple sources into Snowflake, replacing the manual reporting cycle with regularly updated data for analysis.
TitanHQ moved from Amazon Redshift to Snowflake to gain more flexibility and better control over costs. After evaluating alternatives, the team chose Skyvia because it made data extraction easy to customize. It then automated data loading from SugarCRM into Snowflake, reducing the need to write and maintain custom Python scripts.
The Skyvia and Snowflake partnership builds on these practical outcomes: less routine integration work, more business data available for analysis, and a managed way to deliver the results back to the teams that need them.
Ready to get started? Explore Skyvia’s Snowflake integration and start a 14-day trial, or book a live demo with the Skyvia team to discuss your Snowflake integration scenario.
