

Activepieces vs Inngest
A side-by-side comparison of Activepieces and Inngest across 26 workflow orchestration capabilities. Activepieces fully supports 13 of them and Inngest fully supports 19; of the 12 mandatory features, Activepieces covers 8 and Inngest covers 10.
Activepieces
Activepieces is an open-source, self-hostable workflow automation platform and Zapier alternative with a no-code visual builder, hundreds of integrations ('pieces') and AI agent support.
Inngest
Inngest is an event-driven durable execution platform that lets developers write reliable, multi-step background functions and AI workflows in TypeScript, Python or Go, running on serverless, servers or the edge.
Feature comparison
12 of 26 capabilities differ between Activepieces and Inngest.
| Capability | Importance* | ||
|---|---|---|---|
DAG-based workflow definition Define dependencies and execution order Mandatory | Mandatory | Partial | Partial |
Code-first workflows Versionable, testable workflows Mandatory | Mandatory | No | Yes |
Declarative workflow model Predictability, reproducibility Mandatory | Mandatory | Yes | No |
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 | Partial | Yes |
Scheduling (cron / time-based) Automated recurring workflows Depends | Depends | Yes | Yes |
Event-driven execution React to external systems Depends | Depends | Yes | Yes |
Backfills / replays Reprocess historical data Depends | Depends | No | Yes |
Idempotency support Safe retries & replays Mandatory | Mandatory | No | Yes |
Exactly-once semantics Correctness for business workflows Optional | Optional | No | Partial |
Long-running workflows (days/months) Business processes, approvals Depends | Depends | Partial | Yes |
Human-in-the-loop steps Approvals, manual actions Optional | Optional | Yes | Yes |
Dynamic workflows at runtime Conditional execution Depends | Depends | Yes | Yes |
Workflow versioning Safe evolution over time Recommended | Recommended | Yes | Partial |
Distributed execution Scalability Mandatory | Mandatory | Yes | Yes |
High availability scheduler Production reliability Recommended | Recommended | Partial | Yes |
Fault-tolerant execution Crash safety Mandatory | Mandatory | Partial | Yes |
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 | Partial | Partial |
Multi-language SDKs Polyglot systems Optional | Optional | No | Yes |
Deterministic replay Safe recovery & correctness Optional | Optional | No | Partial |
Pluggable execution backends Flexibility Recommended | Recommended | No | No |
* To be considered a complete workflow orchestration tool, a tool must implement the features marked as mandatory according to our assessment.
Spotted an inaccuracy? contact@workflows.guru
Learn more
Read the full profiles, including pros and cons, installation and alternatives.
Related comparisons
- Activepieces vs Airflow
- Inngest vs Airflow
- Activepieces vs Prefect
- Inngest vs Prefect
- Activepieces vs Dagster
- Inngest vs Dagster
- Activepieces vs Argo Workflows
- Inngest vs Argo Workflows
- Activepieces vs Temporal
- Inngest vs Temporal
- Activepieces vs n8n
- Inngest vs n8n
- Activepieces vs Luigi
- Inngest vs Luigi
- Activepieces vs Flyte
- Inngest vs Flyte
- Activepieces vs CrewAI
- Inngest vs CrewAI
- Activepieces vs Kestra
- Inngest vs Kestra
- Activepieces vs LangGraph
- Inngest vs LangGraph
- Activepieces vs Pipedream
- Inngest vs Pipedream
- Activepieces vs Workato
- Inngest vs Workato
- Activepieces vs Cadence
- Inngest vs Cadence
- Activepieces vs Elsa Workflows
- Inngest vs Elsa Workflows
- Activepieces vs Camunda
- Inngest vs Camunda
- Activepieces vs Kubeflow Pipelines
- Inngest vs Kubeflow Pipelines
- Activepieces vs Metaflow
- Inngest vs Metaflow
- Activepieces vs ZenML
- Inngest vs ZenML
- Activepieces vs Apache NiFi
- Inngest vs Apache NiFi
- Activepieces vs Mage
- Inngest vs Mage
- Activepieces vs Tekton
- Inngest vs Tekton
- Activepieces vs Conductor
- Inngest vs Conductor
- Activepieces vs AWS Step Functions
- Inngest vs AWS Step Functions
- Activepieces vs Windmill
- Inngest vs Windmill
- Activepieces vs Concourse
- Inngest vs Concourse
- Activepieces vs Apache DolphinScheduler
- Inngest vs Apache DolphinScheduler
- Activepieces vs Restate
- Inngest vs Restate
- Activepieces vs Hatchet
- Inngest vs Hatchet
- Activepieces vs Trigger.dev
- Inngest vs Trigger.dev