ADF-CDF
Azure Data Factory – Config Driven Framework
No-Code enterprise ETL/ELT Framework, to accelerate and automate the data ingestion into Snowflake using Azure Data Factory.
ADF-CDF is a low-cost, simplified, low-code ELT/ETL framework on top of Microsoft Azure Data Factory for effortless ETL pipelines. It helps in operational efficiency, consistency, performance, and access control while allowing our developers to leverage the Azure Snowflake platform. With this framework, our team of experts spends less time creating and configuring ETL/ELT jobs with minimal code required providing high scalability, flexibility, and security to data integration projects.
Increase in data sources results in as lower than 1.2x investment
Reduces deployment time enabling faster delivery of data pipelines
Increase in cost saving through low cost solution with reduced maintenance effort
Improved performance by configurable Task parallelization
Decrease in issue identification and resolution time
High Total Cost of Ownership (TCO)
Reduces ETL development and maintenance costs with a low-code approach
Operational Challenges
ADF-CDF provides a configurable workflow with comprehensive logging and error handling, enhancing operational efficiency
Performance Bottlenecks
ADF-CDF enables configurable task parallelization and optimized orchestration, improving performance and scalability
Why ADF-CDF?
Low-Code ETL/ELT Framework
Facilitates rapid development and reduces maintenance efforts by minimizing the need for extensive coding.
Configurable Workflows
Allows for flexible and adaptable data integration processes, accommodating various data sources and requirements
Optimized Data Loading
Enhances performance for both full and incremental data loads from flat files and relational databases
Comprehensive Logging and Error Handling
Provides robust monitoring and troubleshooting capabilities, ensuring reliable and efficient data operations
Our Solution
The Azure Data Factory Config-Driven Framework Accelerator is a solution that uses a configuration-driven approach with Snowflake to help automate the ETL workflow for copying data from different sources. While this system has various advantages, like faster complete and incremental load, flexible rerun, and easier pipeline maintenance. Some of the major key offerings include:
- Low code ETL/ELT framework.
- Configurable workflow.
- Optimized for Flat files and RDBMS full and incremental load.
- Out-of-the-box Operational Dashboard.
- Configurable sequential and parallel execution.
- Comprehensive Logging and Error Handling
- Restartable from any point of failure without manual intervention.
- Load Incremental data by using SQL Change Tracking (CT) with schema drift.
Solution Architecture
Trusted by
Take the First Step Toward Smarter Data Integration
Explore how our ADF-CDF framework on Azure can enhance scalability and efficiency.