Prominent Features

Discover the robust features that make Dragonfly a top-tier data quality monitoring tool.


Data Quality Assurance

Receive instant alerts when data issues occur, ensuring reliable data processing.


Data Integrity

Prevent data corruption by halting data processing when issues are detected.


Quality Rules Library

Choose from a library of quality rules across data sources and stages.


Seamless Integration

Easily integrate Dragonfly into existing pipelines using our extensive APIs, and Warehouse and Data Lake integrations.


Data Security

Choose what access you share with Dragonfly and what Metadata is captured, or use access-less integrations.


Event Notifications

Stay informed of the quality issues via SMS, email, or a workflow management system.

Key Concepts

Understand the core concepts that power Dragonfly's High Quality Data monitoring.

Individual steps in data processing, or the different states of the data like processes, ingested data, processed data, and more

Each data processing step is identified as a process. Each stage the data goes through, like ingestion, processed and report is identified as a component. Each type of component has expected behaviour and quality check types in Dragonfly.


Components interconnect based on dependency order to ensure smooth data flow

Relationships between the components show the interdependence of the components fot the purpose of calculating the quality. This is by nature the inverse order of execution represented by the orchestrator tools like Apache Airflow.


Represents your data transformation process, composed of various components

A pipeline is a logical representation of the data processing pipeline, represented as a DAG. Pipelines in Dragonfly are more nuanced than those in orchestration tools like Apache Airflow, in the sense that they also represent logica groups and stages.


Tests that validate the state of processes or data, associated with components

As tests, they are executable expectations of the data quality. There is a library of checks to choose from. There are some built-in checks based on the component type. And it is possible to write your own.


Comprehensive reports generated by health checks, providing insights into your pipeline's health

A quality rating generated by Dragonfly based on the checks applied. It is a comprehensive metrics calculated by weighted resolution of ratings of all dependencies and checks applied.


How Dragonfly Works


Import Data Pipelines

Import the processing stages as components and connect them to build pipelines.


Define Health Checks

Choose form the library, ask the Dragonfly GPT or Write your own checks.


Enjoy Better Data Quality

Experience heightened confidence in your data with our precision-assured reports.