Best Data Engineering Tools for Windows

Consume data from any database, organize it into consistent metrics, and use it with every app. Build your Data and Reporting APIs faster with automated SQL generation, query optimization, access control, consistent metrics definitions, and API design. It takes only days to wrap any data source with a single reference Data API and simplify access to reporting and analytics data across your teams. Make it easy for data engineers and application developers to access the data from any source in a streamlined manner. - The single schema-less Data API endpoint - Review and configure metrics and dimensions in one place via UI - Data model visualization to make faster decisions - Data Export management scheduling AP Ready-to-use Report Builder and JavaScript components for charting libraries (Highcharts, BizCharts, Chart.js, etc.) makes it easy to embed data-rich functionality into your products. And you will not have to make custom report queries anymore!

Domo’s AI and data platform business is now part of Progress Software. Domo's cloud-native AI data readiness platform complements and significantly broadens Progress' data platform offerings, creating powerful synergies to deliver innovative, secure and scalable AI data readiness solutions worldwide. Together, these capabilities will help customers turn fragmented enterprise data and knowledge into governed, AI-ready intelligence, improving the security, governance and cost of AI-powered initiatives. Domo is the agentic platform for the intelligent enterprise, helping organizations connect, govern, activate, and distribute data and AI. Domo works with cloud data platforms including Snowflake, BigQuery, and Databricks to turn governed data into AI agents, apps, workflows, dashboards, and analytics. Its data foundation, activation, and distribution layers help teams build and deliver intelligence where work happens, with governance, security, and access controls across data and AI.

Kestra is an open-source, event-driven orchestrator that simplifies data operations and improves collaboration between engineers and business users. By bringing Infrastructure as Code best practices to data pipelines, Kestra allows you to build reliable workflows and manage them with confidence. Thanks to the declarative YAML interface for defining orchestration logic, everyone who benefits from analytics can participate in the data pipeline creation process. The UI automatically adjusts the YAML definition any time you make changes to a workflow from the UI or via an API call. Therefore, the orchestration logic is defined declaratively in code, even if some workflow components are modified in other ways.