LangGraph vs ZenML

A side-by-side comparison of LangGraph and ZenML across 26 workflow orchestration capabilities. LangGraph fully supports 21 of them and ZenML fully supports 13; of the 12 mandatory features, LangGraph covers 10 and ZenML covers 9.

LangGraph

LangGraph is a stateful, graph-based orchestration framework for building, managing, and deploying long-running agentic LLM applications and workflows.

Features fully supported21 / 26

Mandatory features: 10 / 12View profile

ZenML

ZenML is an open-source MLOps framework that lets teams write ML and AI pipelines in Python once and run them on any orchestrator and infrastructure stack.

Features fully supported13 / 26

Mandatory features: 9 / 12View profile

Feature comparison

9 of 26 capabilities differ between LangGraph and ZenML.

Show only differencesChange tools

Capability	Importance*	LangGraph	ZenML
DAG-based workflow definition Define dependencies and execution order Mandatory	Mandatory	Yes	Yes
Code-first workflows Versionable, testable workflows Mandatory	Mandatory	Yes	Yes
Declarative workflow model Predictability, reproducibility Mandatory	Mandatory	Partial	Partial
Task dependency resolution Correct execution order Mandatory	Mandatory	Yes	Yes
Persistent workflow state Crash recovery, observability Mandatory	Mandatory	Yes	Yes
Task retries Handle transient failures Mandatory	Mandatory	Yes	Yes
Retry policies (backoff, limits) Avoid cascading failures Recommended	Recommended	Yes	Yes
Scheduling (cron / time-based) Automated recurring workflows Depends	Depends	No	Partial
Event-driven execution React to external systems Depends	Depends	Yes	Partial
Backfills / replays Reprocess historical data Depends	Depends	Yes	No
Idempotency support Safe retries & replays Mandatory	Mandatory	Partial	Partial
Exactly-once semantics Correctness for business workflows Optional	Optional	No	No
Long-running workflows (days/months) Business processes, approvals Depends	Depends	Yes	Partial
Human-in-the-loop steps Approvals, manual actions Optional	Optional	Yes	Partial
Dynamic workflows at runtime Conditional execution Depends	Depends	Yes	Partial
Workflow versioning Safe evolution over time Recommended	Recommended	Yes	Yes
Distributed execution Scalability Mandatory	Mandatory	Yes	Yes
High availability scheduler Production reliability Recommended	Recommended	Yes	Partial
Fault-tolerant execution Crash safety Mandatory	Mandatory	Yes	Partial
Observability (logs, states, UI) Debugging & ops Mandatory	Mandatory	Yes	Yes
Workflow-level visibility Understand end-to-end runs Mandatory	Mandatory	Yes	Yes
Task isolation Failure containment Mandatory	Mandatory	Yes	Yes
Native Kubernetes support Modern infra compatibility Depends	Depends	Yes	Yes
Multi-language SDKs Polyglot systems Optional	Optional	No	No
Deterministic replay Safe recovery & correctness Optional	Optional	Yes	No
Pluggable execution backends Flexibility Recommended	Recommended	Yes	Yes

* To be considered a complete workflow orchestration tool, a tool must implement the features marked as mandatory according to our assessment.

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Read the full profiles, including pros and cons, installation and alternatives.

LangGraph

ZenML

LangGraph vs ZenML

LangGraph

ZenML

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