Case Study: Dayton Freight Accelerates Data Integration Across Diverse Platforms with Etlworks

Dayton Freight Powers Real-Time CDC and Scalable ETL Workflows with Etlworks.

Introduction

Dayton Freight, a leader in regional transportation and logistics, relies on Etlworks to seamlessly integrate data across multiple platforms, including AS400, Apache Kafka, APIs, Greenplum, Postgres, and more. By leveraging Etlworks’ robust CDC streaming and ETL capabilities, Dayton Freight ensures real-time data synchronization and efficient data warehousing, enabling actionable insights and enhanced operational efficiency.

The Challenge

Dayton Freight faced complex challenges in managing their data integration workflows:

Diverse Data Sources and Destinations: Required seamless integration with legacy systems (AS400), modern platforms (Kafka), cloud databases (Greenplum, Postgres), APIs, and more.

Real-Time Streaming: Needed reliable Change Data Capture (CDC) to stream data from AS400 and Kafka into downstream systems.

Scalable ETL Pipelines: Required efficient data warehousing workflows to load data into Greenplum and Postgres at scale.

Unified Data Ecosystem: Sought a solution capable of bridging the gap between legacy and modern data platforms.

Why Etlworks

Dayton Freight selected Etlworks for its ability to handle diverse and complex data integration needs:

CDC Streaming: Enabled real-time data streaming from AS400 and Kafka into Greenplum and Postgres.

Comprehensive Integration: Supported seamless workflows across APIs, AS400, Kafka, Greenplum, Postgres, and other platforms.

Scalable ETL Workflows: Delivered high-performance pipelines for data warehousing and analytics.

Flexible Architecture: Unified legacy and modern systems into a cohesive data ecosystem.

Ease of Use: Simplified pipeline creation and management with a user-friendly interface.

The Solution

Etlworks implemented a robust and scalable data integration framework for Dayton Freight:

Real-Time CDC Pipelines: Enabled low-latency data streaming from AS400 and Kafka into downstream systems.

ETL Workflows for Data Warehousing: Designed scalable workflows to load and transform data into Greenplum and Postgres.

Unified Integration Platform: Connected diverse data sources and destinations, including APIs, legacy systems, and modern databases.

Scalable and Reliable Infrastructure: Delivered consistent performance across high-volume pipelines.

Results

Real-Time Data Synchronization: Achieved reliable CDC streaming from AS400 and Kafka into Greenplum and Postgres.

Unified Data Ecosystem: Integrated legacy systems with modern platforms, creating a cohesive data environment.

Scalable Performance: Supported high data volumes and complex workflows with consistent reliability.

Improved Efficiency: Streamlined data integration processes, reducing operational complexity and overhead.

Key Takeaways

Real-Time CDC Streaming: Delivered reliable data synchronization from AS400 and Kafka into downstream systems.

Comprehensive Integration: Unified diverse data sources and destinations, including APIs, legacy systems, and modern databases.

Scalable ETL Workflows: Powered efficient data warehousing pipelines into Greenplum and Postgres.

Unified Ecosystem: Bridged the gap between legacy and modern platforms seamlessly.

Enhanced Efficiency: Simplified complex data integration workflows, enabling faster insights.

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.