JamJet

Framework Comparison

JamJet vs LangGraph vs CrewAI vs AutoGen vs Google ADK — feature matrix across execution, durability, observability, eval, and scale.

Last updated: 2026-04-15 · JamJet v0.5.0 · Corrections welcome

Built-in Via plugin~ Partial Not supported In progress

Which one is best for what?

  • Plain Python — fastest start, lowest guarantees. Great for prototypes and one-off scripts.
  • LangGraph — graph orchestration, familiar patterns, optional durability via checkpointers.
  • JamJet — Python mental model with durability by default and stronger runtime guarantees.
  • CrewAI / AutoGen — useful abstractions for some multi-agent patterns, but different emphasis on reliability.
  • Google ADK — tight Gemini integration, co-developed A2A, fast-moving with strong Google Cloud support. Best for teams building on Google's AI stack.

If you like LangGraph's Python workflow model but want durability, replay, typed validation, and runtime-enforced limits built in, JamJet is the closest conceptual move. See the LangGraph migration guide.

Core execution

FeatureJamJetLangGraphCrewAIAutoGenGoogle ADK
Graph-based workflow~ Sequential/hierarchical Sequential, parallel, loop agents
Async execution
Local in-process runner
Typed state Pydantic~ TypedDict Dict~ Dict~
State validation at every step
Conditional routing Inline predicates Edge functions~ Process type
Parallel branches type: parallel
Cycle / loop support~

Durability & reliability

FeatureJamJetLangGraphCrewAIAutoGenGoogle ADK
Durable execution (crash recovery) Rust runtime Checkpointers
Event sourcing Native
Automatic retry with backoff YAML config Manual Manual Manual~ Manual
Human-in-the-loop / pause type: wait interrupt_before~
Resume from any checkpoint Requires saver
Timeout per step~~~

Observability

FeatureJamJetLangGraphCrewAIAutoGenGoogle ADK
Structured event log Per-step events~ Callbacks~ verbose text~
Execution inspection CLI jamjet inspect
Event timeline
OpenTelemetry tracing LangSmith Built-in
Time-travel debugging
Token/cost attribution
Web inspector/dashboard Web Companion ADK Web UI

Tool & protocol integration

FeatureJamJetLangGraphCrewAIAutoGenGoogle ADK
MCP client (use any MCP server) Native Via adapter Via adapter Via adapter Native
MCP server (expose your tools)
A2A cross-agent calls Client + server Co-developed spec
OpenAI function calling
Custom Python tools @tool decorator
Tool retry on error Node-level config Manual Manual Manual~

Eval & testing

FeatureJamJetLangGraphCrewAIAutoGenGoogle ADK
Built-in eval harness pytest-based
LLM-as-judge scoring LlmJudgeScorer
Assertion scoring AssertionScorer
Latency budgets LatencyScorer
Cost budgets CostScorer
Dataset replay~
CI exit code on regression --fail-under~
Eval as a workflow node type: eval

Developer experience

FeatureJamJetLangGraphCrewAIAutoGenGoogle ADK
YAML workflow authoring
Python decorator API @wf.step
Project templates jamjet init --template
Local dev server jamjet dev
Workflow validation CLI jamjet validate
Multi-model support Any OpenAI-compat~ Primarily Gemini
Local models (Ollama, etc.)~

Production & scale

FeatureJamJetLangGraphCrewAIAutoGenGoogle ADK
Runtime languageRustPythonPythonPythonPython
Polyglot SDKPython (TS )Python, JSPythonPython, .NETPython
Kubernetes-ready Stateless binary
Managed cloud offering LangGraph Cloud Vertex AI
Streaming~
Open source Apache-2.0 MIT MIT CC-BY-4 Apache-2.0

note: See Benchmarks for measured latency comparisons with methodology and raw results. Migration guides: from LangGraph, from CrewAI, from OpenAI SDK.

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