Head-to-head · LLM Application Development Frameworks
Apache Burr vs Flowise
Apache Burr leads on 3 checks, Flowise on 0, and 2 are even. Who comes out ahead on the 5 yes/no, price and count checks where we have data for both products. The editor score weighs everything else too.
Our verdict
- Highest scoreApache Burr · 8.8/10
- Free planboth
- Most featuresApache Burr · 3 of 5
Apache Burr scores higher on our rubric for llm application development frameworks: 8.8 against 8.6 out of 10; our editors rank them #6 and #8.
Apache Burr offers rag support; Flowise doesn't publish it. Apache Burr offers agent and tool use; Flowise doesn't publish it. Apache Burr offers workflow graphs; Flowise doesn't publish it.
Apache Burr is the better fit for stateful, inspectable workflow applications. Flowise is the better fit for reviewing or maintaining existing Flowise projects.
- Apache Burr fits best
Stateful, inspectable workflow applications
- Flowise fits best
Reviewing or maintaining existing Flowise projects
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Side by side
| Feature | Apache Burr 8.8/10 Visit ↗ | Flowise 8.6/10 Visit ↗ |
|---|---|---|
| At a glance | ||
| Editor score | 8.8 | 8.6 |
| Ranking | #6 in LLM Application Development Frameworks | #8 in LLM Application Development Frameworks |
| Best for | Stateful, inspectable workflow applications | Reviewing or maintaining existing Flowise projects |
| Pricing model | Free | Free plan + paid |
| Starting price | Not published | $35/mo |
| Free plan | ✓ | ✓ |
| Free trial | — | — |
| Deployment | Self-hosted | Cloud, Self-hosted |
| Platforms | Linux, macOS, Windows | Web |
| Support | Community, Docs | Community, Docs, Email |
| Integrations | 15 integrations | 6 integrations |
| Built for | Solo, Small business, Mid-market, Enterprise | Solo, Small business, Mid-market, Enterprise |
| Features Apache Burr 3/5 · Flowise 0/5 | ||
| RAG support | ✓ (best) | Not published |
| Agent and tool use | ✓ (best) | Not published |
| Workflow graphs | ✓ (best) | Not published |
| Prompt optimization | Not published | Not published |
| JavaScript/TypeScript SDK | — | Not published |
| Specs | ||
| Primary language | Python | Not published |
| Open-source license | Apache-2.0 | Not published |
| Our review | ||
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| Our verdict | Apache Burr is an open-source Python framework for building applications from actions, transitions, and explicit state. It is aimed at developers orchestrating chatbots, agents, conversational retrieval workflows, and other applications… Read the review → |
Flowise was an open-source framework for building AI agents, chatbots, and LLM workflows with visual tools. Its Assistant, Chatflow, and Agentflow builders were aimed at developers and teams who wanted to assemble workflows visually while… Read the review → |
Strengths and trade-offs
Apache Burr — where it wins
- Immutable state, persistence, and resumable human-input pauses
- Parallel actions and branches support complex workflows
- Burr UI exposes execution telemetry for inspection and debugging
Where it doesn't
- Python-focused; no official JavaScript or TypeScript SDK is identified
- Requires developers to implement LLM calls within actions
- Fewer ready-made model integrations and agent capabilities than some alternatives
Flowise — where it wins
- Visual builders cover assistants, chatflows, and agentflows
- Supports retrieval, coordinated agents, approvals, and execution traces
- Offers APIs, SDKs, CLI, and embedded chat
Where it doesn't
- Feature development ceased and the repository was archived in 2026
- Official core-team operations ended on August 31, 2026
- Integration descriptions name broad categories rather than specific products
- Apache Burr8.8/10 · Free plan
An open-source Python framework for stateful, inspectable workflow applications.
Visit Apache BurrFull verdict → - Flowise8.6/10 · Free plan · paid from $35/mo
A visual agent-building framework whose development and official operations have ended.
Explore FlowiseFull verdict →
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All LLM application development frameworks comparisons → · Full ranking →
Reviewed by iTechGuides Editors · Editorial team · Updated Oct 2026
Last updated · How we research and update



