DataRow

DataRow

DataRow is an open-source data integration and ETL tool for managing data pipelines. It provides a visual interface to build data workflows without coding and supports connecting to various data sources and destinations.

DataRow: Open-Source Data Integration & ETL Tool

An open-source data integration and ETL tool for managing data pipelines, providing a visual interface to build data workflows without coding, and supporting various data sources and destinations.

What is DataRow?

DataRow is an open-source data integration and ETL (extract, transform, load) tool for managing data pipelines. It provides a user-friendly visual interface to build data workflows without coding.

Key features of DataRow:

  • Connect to various data sources like databases, APIs, files etc. Supports Postgres, MySQL, SQL Server, Snowflake and many other databases.
  • Transform and cleanse data using built-in transformations or writing SQL or Python code.
  • Load transformed data into data warehouses, lakes or other destinations.
  • Schedule and orchestrate data workflow runs.
  • Monitoring and alerts for data pipelines.
  • Version control data workflow changes.
  • Community supported and available under Apache license.

With its code-free GUI for building data transformations and connectivity to many data sources and destinations out of the box, DataRow makes it easy for both technical and non-technical users to manage their data integration needs without writing code.

DataRow Features

Features

  1. Visual interface for building data workflows
  2. Supports various data sources and destinations
  3. Drag-and-drop functionality for easy pipeline construction
  4. Scheduling and orchestration of data pipelines
  5. Monitoring and error handling capabilities
  6. Supports data transformations and data quality checks
  7. Collaborative features for team-based data integration

Pricing

  • Open Source

Pros

Ease of use with no coding required

Supports a wide range of data sources and destinations

Open-source and community-driven development

Scalable and can handle large data volumes

Provides a visual interface for pipeline management

Cons

Limited advanced features compared to enterprise-grade ETL tools

Potential performance issues with complex data pipelines

Reliance on community support for troubleshooting and feature requests

Steeper learning curve for non-technical users

Official Links

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