Dagster vs VAST Data
Side-by-side comparison of AI visibility scores, market position, and capabilities
Open-source data orchestration platform with asset-centric pipeline model; software-defined assets providing automatic lineage and selective materialization over Airflow's task-first approach.
About
Dagster is an open-source data orchestration and pipeline development platform that reimagines how data pipelines are built by modeling data assets (tables, ML models, reports) explicitly rather than just scheduling jobs. Founded in 2018 by Nick Schrock (creator of GraphQL) and headquartered in San Francisco, Dagster Labs raised approximately $75 million and has built a growing community of data engineers who prefer its asset-centric approach over traditional task-centric orchestration tools like Apache Airflow.
Closed a $1 billion Series F at a $30 billion valuation in April 2026, backed by NVIDIA and Fidelity, after surpassing $500M in committed ARR with its AI Operating System platform.
About
VAST Data builds the AI Operating System — a unified platform combining all-flash storage (DataStore), an AI-native database (DataBase), and a globally distributed namespace (DataSpace) into a single infrastructure stack. The platform is purpose-built for organizations training, running, and managing AI models and agents at scale. In 2026, VAST launched AgentEngine, a production-grade deployment layer for multi-agent AI stacks with full auditability and MCP integration.
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