dagster
★ 16.3k
vs
Flowise
★ 55.5k
dagster vs Flowise
dagster: Dagster is a data orchestrator purpose-built for data platforms in the MLOps era, helping users define, develop, and operate data assets. It offers a powerful programming model, local development experience, and a robust UI for observing and debugging pipelines in production.; Flowise: Flowise is an open-source low-code tool for building custom AI agents and LLM applications. It provides a drag-and-drop UI to easily construct complex AI workflows visually.
01
TL;DR
dagsterWorkflow Automation · ★ 16.3k
When to choose:
- You need an asset-centric data and AI orchestration platform that tracks data dependencies, partition lineages, and observability in Python.
- You want local development ergonomics, declarative asset definitions, and unified orchestration across dbt, ML models, and data pipelines.
When to skip:
- You need simple, lightweight agent conversation loops; Dagster is an enterprise data engineering orchestrator, not a chat bot loop.
- You need durable function workflows with arbitrary sleeps and human-in-the-loop approvals without asset abstractions; Temporal is simpler for that.
FlowiseWorkflow Automation · ★ 55.5k
When to choose:
- You want an intuitive visual drag-and-drop canvas for building LangChain/LlamaIndex agents, multi-agent workflows, and RAG pipelines without code.
- You need an embeddable chat widget, API endpoints, and a low-code UI for rapid AI application prototyping.
When to skip:
- You need a long-term actively maintained project; the Flowise repository was archived in August 2026 and reached end-of-life.
- You require code-first, type-safe Python orchestration with deterministic checkpointing; Pydantic AI or Temporal are better choices.
02
Side-by-Side Comparison
Field
dagsterFlowiseCategory
Workflow Automation
Workflow Automation
Stars
★ 16.3k
★ 55.5k
License
Apache-2.0
NOASSERTION
Install Command
pip install dagster dagster-webserver
npm install -g flowise
Updated
1d ago
2mo ago
Open Source
Yes
Yes
Tags
Data Orchestration, MLOps, Data Pipelines
AI Agents, Visual Programming, LLM
03
Features
dagster01Software-defined Assets
02Declarative Programming Model
03Powerful Local Development
04Robust Operational UI (Dagit)
05Extensive Integrations
Flowise01Visual drag-and-drop interface for building AI agents and LLM apps.
02Supports a wide range of LLMs, embeddings, and tools through component integrations.
03Enables low-code/no-code development for rapid AI application creation.
04Flexible self-hosting options across various cloud providers and platforms.
05Modular architecture with distinct server, UI, and component packages.
04
Use Cases
dagster↳Building reliable data platforms
↳Developing MLOps workflows
↳Automating data analytics and reporting
Flowise↳Rapidly prototyping and developing LLM-powered applications.
↳Creating custom AI chatbots and conversational interfaces.
↳Integrating advanced AI capabilities into existing software systems.
05
Best For
dagsterMost PopularEssentialTrending
Flowise—
FAQ
FAQ
What is the difference between dagster and Flowise?
Both dagster and Flowise are in the Workflow Automation category. dagster has 16.3k stars, while Flowise has 55.5k stars.
Which is better, dagster or Flowise?
The best choice depends on your use case. Choose dagster if Building reliable data platforms, and Flowise if Rapidly prototyping and developing LLM-powered applications..
Is dagster free or open source?
Yes, dagster is open source on GitHub (Apache-2.0).
Is Flowise free or open source?
Yes, Flowise is open source on GitHub (NOASSERTION).
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