Tourmo.ai

Introduction

Tourmo.ai, an AI-powered mobility intelligence platform, depends on fast, reliable data pipelines to deliver real-time insights and advanced analytics. To support a growing ecosystem of MySQL data sources and cloud destinations, Tourmo.ai uses Etlworks to implement robust CDC-based streaming and batch ETL workflows into Snowflake.

The Challenge

Tourmo.ai needed a solution that could handle a variety of data integration requirements:

• Real-Time Data Delivery: Stream change data from multiple MySQL databases into Snowflake with minimal latency.

• Multi-Source Integration: Manage batch pipelines across several MySQL environments with varying schemas and volumes.

• Cloud Analytics: Enable analytics teams to access up-to-date, centralized data for AI models and business reporting.

• Reliability at Scale: Ensure performance and consistency across both real-time and batch workflows without manual maintenance.

Why Etlworks

Tourmo.ai selected Etlworks for its combination of flexibility, scalability, and ease of use:

• Change Data Capture (CDC): Enabled continuous streaming from MySQL into Snowflake for real-time visibility.

• Batch ETL: Supported scheduled jobs to extract, transform, and load large volumes of data from disparate sources.

• Unified Platform: Simplified management by consolidating streaming and batch integration into a single environment.

• Cloud-First Architecture: Native support for Snowflake and scalable cloud pipelines aligned with Tourmo.ai’s infrastructure.

• Minimal Overhead: Allowed the team to build and maintain complex workflows without custom development.

The Solution

Etlworks provided Tourmo.ai with a complete data integration framework:

• CDC Pipelines: Near real-time replication from transactional MySQL databases into Snowflake using high-watermark logic and error recovery.

• Batch Workflows: Configured scheduled flows to move data from additional MySQL environments into Snowflake for reporting and enrichment.

• Reusable Components: Created templates and shared connections to speed up deployment and streamline pipeline updates.

• Monitoring and Logging: Enabled proactive error tracking and status visibility across all flows.

Results

• Real-Time Visibility: Business and technical users now have continuous access to critical data in Snowflake.

• Scalable Operations: Easily expanded integrations to support new MySQL sources without re-engineering.

• Unified Data Environment: Combined real-time and batch data into a single warehouse for modeling, dashboards, and forecasting.

• Lower TCO: Reduced the need for custom scripts and third-party tools, cutting integration costs and complexity.

Key Takeaways

• Reliable CDC Streaming from MySQL to Snowflake for real-time insights.

• Efficient Batch ETL pipelines support diverse reporting and analytics needs.

• Unified Architecture brings streaming and batch processing together.

• Scalable, Cloud-Ready Platform adapts to growth without added complexity.

Ready to tackle your most complex data challenges? Discover how Etlworks can transform your data integration workflows. Start your free trial today or request a demo.