Seamless Snowflake Integration for Any Source
Connect databases, APIs, files, and SaaS apps to Snowflake using a single, powerful platform. From real-time streaming to scheduled ETL. Etlworks does it all.
Why it matters: Snowflake is a popular destination for modern data pipelines. Etlworks simplifies integration by supporting a wide range of sources and use cases, enabling teams to load and operationalize data with minimal effort.
- Get Started with Snowflake
- Snowflake Case Studies
- SOC 3 Report (SOC 2 Report available after NDA)
- Security Policies
Get in Touch
Why Etlworks
All-in-One Platform: Use one tool for ETL, reverse ETL, CDC, API, and SaaS integration with Snowflake.
Real-Time and Batch: Stream data to Snowflake using Change Data Capture or run traditional ETL jobs—your choice.
No-Code or Full Control: Build flows visually or script them with SQL and JavaScript for complete flexibility.
Auto Schema Mapping: Automatically map source schemas to Snowflake tables, even for deeply nested data.
Prebuilt Templates: Use ready-to-run templates to integrate Snowflake with virtually any system.
High Performance: Load large volumes of data into Snowflake with support for staging, parallelization, and auto-partitioning.
Production Ready: Built-in logging, monitoring, scheduling, and alerting make it easy to run Snowflake pipelines at scale.
Zero Maintenance: Etlworks pipelines run unattended, handling retries, schema changes, and errors automatically.
How Companies Use Etlworks for Snowflake Integration
Streams real-time CDC data from over 1,500 MySQL databases into Snowflake using Etlworks' scalable architecture.
Read the Case Study

Uses Etlworks for real-time and batch pipelines into Snowflake, managing data across hundreds of student housing properties.
Read the Case Study

Automates complex third-party API integrations into Snowflake using Etlworks' zero-maintenance data pipelines.
Read the Case Study
Implements fast, reliable ETL from SQL Server into Snowflake using advanced techniques to scale across multiple tables.
Read the Case Study