open source data engineering platform - AI tools

Dlytica offers comprehensive data engineering, data science, and AI solutions, including generative AI, IoT, and RPA, to drive business growth and efficiency.

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Dflux is a unified data science platform that offers end-to-end data engineering and intelligence with no-code machine learning capabilities. It enables seamless data integration, streamlined workflow management, and accelerated insights for data-driven decision-making.

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Dagster is a data orchestrator designed for data engineers to build and manage data platforms. It enables rapid development, testing, and confident deployment of data pipelines.

• Paid
• From 10$

Databricks is a unified data intelligence platform that combines data, analytics, and AI. It helps organizations leverage their data for generative AI applications, democratize insights, and reduce costs.

• Usage Based

Ellie is an AI-powered enterprise data modeling tool that connects business and data teams, simplifying engineering workflows and accelerating analytics projects.

• Free Trial

Rivery is a cloud-based data platform that enables businesses to build, orchestrate, and optimize data pipelines with AI assistance, low-code/no-code interfaces, and seamless integrations to hundreds of data sources.

• Usage Based

DataExpert.io Academy offers comprehensive data engineering training with AI-driven feedback, expert insights, and hands-on cloud experience to advance your career.

• Other
• From 125$

HPCC Systems is an open source big data platform designed for high-speed data engineering, analytics, and machine learning. It features robust performance, secure processing, and seamless scalability for building and managing data lakes.

• Free

Datascale is a comprehensive SQL analysis and data modeling platform that simplifies complex database relationships through automated visualization and lineage tracking, helping teams better understand and manage their data assets.

• Freemium
• From 10$

Acceldata provides a unified data observability platform to ensure data quality, prevent failures, and control costs for hybrid and multi-cloud data stacks. It helps businesses build a strong AI foundation with high-quality, reliable data.

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