Hatchet vs Kestra (2026)

The customer's agents and tools run here, but Hatchet does not supply them. Cookbooks show agents built with the Claude Agent SDK and the OpenAI Agents SDK running as Hatchet tasks, and any task can call an outside API. There is no connector catalog, custom tool route or framework for authenticated actions of Hatchet's own, so the tools and credentials are the customer's code. Webhook integrations with GitHub, Stripe and Slack start runs.

Sourcedocs.hatchet.run/cookbooks/hatchet-claude-agent-sdk-trusted-envread 2026-09-23

The AI Agent task takes tools of Kestra's own, including any Kestra task or flow called as a tool (KestraTask, KestraFlow), web search (Google Custom Search, Tavily), MCP clients over SSE, stdio and streamable HTTP, and another agent as a tool, and the platform ships over 2,000 plugins for databases, cloud services, messaging and business systems with managed credentials through secrets.

Sourcekestra.io/docs/ai-tools/ai-agentsread 2026-09-25

Tasks compose into DAG workflows and durable tasks that can spawn child tasks, so Hatchet works as a workflow engine. They carry retry policies, timeouts, cancellation, durable sleeps and event waits, along with concurrency control, rate limits, priority, batch tasks and bulk triggering. Workers run them in Python, TypeScript, Go and Ruby.

Sourcedocs.hatchet.run/v1/directed-acyclic-graphsread 2026-09-23

Kestra is a workflow engine whose flows, declared in YAML, run tasks through flowable control primitives (Sequential, Parallel, Loop, LoopUntil, Switch, If, DAG and Subflow), with retries, error handling and backfills. For agents, an AI Agent task decides which tools and tasks to run and in what order, a parent agent can delegate to a child agent wrapped as a tool, and an A2A client forwards work to a remote agent.

Sourcekestra.io/docs/workflow-components/tasks/flowable-tasksread 2026-09-25

Work wakes on its own through cron runs, scheduled runs, events that trigger workflows, and webhook endpoints that start runs from GitHub, Stripe, Slack or any sender, and one service can trigger work in another.

Sourcedocs.hatchet.run/v1/webhooksread 2026-09-23

Flows declare Schedule (cron), Flow (another flow finishing), Webhook, Polling and Realtime triggers, and an MCP Tool trigger registers a flow as a tool an outside agent can call.

Sourcekestra.io/docs/workflow-components/triggersread 2026-09-25

There is no retrieval structure that Hatchet maintains over the customer's corpus. Its cookbooks run document pipelines as tasks, but the parsing, indexing and retrieval are the customer's own code.

Sourcedocs.hatchet.run/cookbooks/pdf-pipelineread 2026-09-23

The IngestDocument task chunks and embeds the customer's documents into an embeddings store (Kestra's own KV Store, or Chroma, Elasticsearch, PGVector, Pinecone, Qdrant, Weaviate and others), and the RAG ChatCompletion task and EmbeddingStoreRetriever query that store so an agent answers from the customer's data. The embeddings persist across runs.

Sourcekestra.io/docs/ai-tools/ai-rag-workflowsread 2026-09-25

State lasts within one run. Hatchet is durable by default and stores every task, DAG, event and agent invocation in a durable event log, so a durable task replays its completed steps and carries on after a failure. But the checkpointed state only lets the same run finish and carries nothing into the next run. Sticky worker assignment keeps local memory on one worker for a workflow's tasks, which is placement, not a store. There is no state store that persists across runs, keyed per user, conversation or entity, for agent memory.

Sourcedocs.hatchet.run/v1/durable-executionread 2026-09-23

Agents built in Kestra remember information across executions through a memory plugin. The KestraKVStore memory saves the chat messages from the agent's own turns to a namespace KV entry keyed by memoryId, with PostgreSQL and Redis memories as alternatives, so one conversation or customer can be deleted without touching the rest. A TTL sets its expiry, drop set to AFTER_TASKRUN deletes it after use, and scheduled purges cover KV pairs. KV pairs can be created, edited and deleted in the Kestra UI, through tasks and through the REST API.

Sourcekestra.io/plugins/plugin-ai/memory/io.kestra.plugin.ai.memory.kestrakvstoreread 2026-09-25

Holding for a person runs on durable waits that the customer's code calls. A durable event wait suspends a task until a matching user event arrives, filtered with CEL expressions, or until a timeout passes, and workflows can be paused and resumed. This is a general wait put to use for approval. There is no approval step, approver identity, review screen or policy guardrail of Hatchet's own.

Sourcedocs.hatchet.run/v1/durable-event-waitsread 2026-09-23

A Pause task holds a flow at a chosen step, for output validation or manual approval, until a person resumes it from the UI or API. Approval chains route decisions to specific users or teams, with audit logs recording who approved or rejected each request and why, and Human-in-the-Loop Approvals with custom inputs come in the Enterprise Edition.

Sourcekestra.io/docs/use-cases/approval-processesread 2026-09-25

SOC 2 Type II applies from the free Developer plan, and HIPAA with audit logs from the Scale plan. Tenants separate environments, each with its own users. Hatchet Cloud signs users in with Google or GitHub OAuth, enterprises can set up custom SSO, and Enterprise includes SSO and audit logging.

Sourcehatchet.run/pricingread 2026-09-23

The Enterprise Edition includes SSO, LDAP and SCIM, role based access control with a permissions reference, policies, and multi tenant storage isolation, with audit logs and a secrets manager as supporting controls. Kestra Cloud is SOC 2 compliant.

Sourcekestra.io/pricingread 2026-09-25

Every task, DAG, event and agent invocation is recorded in a durable event log shown in the dashboard, with real time monitoring, alerting and task logs. Traces export through OpenTelemetry, Prometheus metrics are exposed, audit logs are kept from the Scale plan, and data retention is set by plan, at 3 days on Team and 7 on Scale.

Sourcedocs.hatchet.run/v1/opentelemetryread 2026-09-23

Every execution is recorded for step by step inspection. The Executions view shows status, logs, outputs and metrics per task through Gantt and Topology views, AI Agent tasks can log each model request and response, and the Enterprise Edition adds audit logs recording every action by users and service accounts plus log shipping to an external store.

Sourcekestra.io/docs/ui/executionsread 2026-09-25

Customers can self host in their own infrastructure on Docker Compose or Kubernetes under an MIT license, and there is an embedded mode. Hatchet Cloud is the managed service, and Enterprise offers custom deployment and bring your own cloud.

Sourcegithub.com/hatchet-dev/hatchetread 2026-09-23

The open source edition is Apache 2.0 licensed and self hosts on the customer's infrastructure, cloud or Kubernetes, and the Enterprise Edition runs on cloud, on premises or air gapped, with Kestra Cloud as the managed option.

Sourcekestra.io/pricingread 2026-09-25

Starting points come as cookbooks for webhook handlers for GitHub, Stripe and Slack, document pipelines, email flows and agents built on the Claude Agent SDK and OpenAI Agents SDK, plus skills that coding agents can install. These are examples a developer builds from, not a catalog of agents a customer adopts.

Sourcedocs.hatchet.run/cookbooksread 2026-09-23

Kestra publishes Blueprints, a searchable catalog of validated, documented flows, including AI agent and RAG flows, that a buyer adopts into a namespace with one click from inside the product and then adjusts; the Enterprise Edition adds custom blueprints, an organization's own approved set.

Sourcekestra.io/docs/concepts/blueprintsread 2026-09-25

There is no model in Hatchet for the customer to choose. The model lives in the customer's own agent code, and the cookbooks use the OpenAI Agents SDK and the Claude Agent SDK, while Hatchet schedules and records the tasks whatever the model is. It works with any model only because the model belongs to someone else, and it offers no model selection of its own.

Sourcedocs.hatchet.run/cookbooks/hatchet-openai-agents-sdk-trusted-envread 2026-09-23

Each AI task takes its model through Kestra's provider property, so the customer picks among providers of Kestra's own for Anthropic, OpenAI, Azure OpenAI, Amazon Bedrock, Google Gemini and Vertex AI, Mistral, DeepSeek, Ollama, OpenRouter and others, and an Enterprise policy can set the provider across a namespace.

Sourcekestra.io/docs/ai-tools/ai-agentsread 2026-09-25

Official SDKs for Python, TypeScript, Go and Ruby make the platform callable from outside, alongside a REST and gRPC API for triggering and inspecting runs and the hatchet CLI. A local MCP server bundled with the CLI lets coding agents trigger runs, inspect status and events, and list workers.

Sourcedocs.hatchet.run/v1/using-coding-agentsread 2026-09-23

Kestra is API first, with every UI action available through its REST API, and ships official SDKs for Java, Python, JavaScript and TypeScript, and Go, a Terraform provider, and custom plugin development. Its MCP servers expose flows as named tools over HTTP for outside agents, with authentication set per server.

Sourcekestra.io/docs/api-reference/kestra-sdkread 2026-09-25

When a run goes wrong, it can be replayed from the durable event log, retried or canceled in bulk, and inspected by a coding agent through the MCP server. That helps with debugging, not testing. There is no evaluation harness, scored test cases or quality gate of Hatchet's own.

Sourcedocs.hatchet.run/v1/durable-executionread 2026-09-23

Unit Tests in the Enterprise Edition run test suites that mock tasks and assert on flow behavior, so a change can be checked before production without real side effects. Those assertions check that the flow behaves as configured, and Kestra does not describe an evaluation harness, scored test cases or a judge for agent output.

Sourcekestra.io/docs/enterprise/governance/unit-testsread 2026-09-25

The agent operates no browser or desktop, and Hatchet has no browser automation environment of its own. It schedules and runs the customer's tasks on the customer's workers.

Sourcedocs.hatchet.run/v1/using-coding-agentsread 2026-09-23

The AI Agent's tools are Kestra tasks and flows, web search, MCP clients and other agents, none of them a browser or desktop it operates. Kestra does not describe a browser automation environment or a hosted browser workload, though script tasks run any code the customer supplies.

Sourcekestra.io/docs/ai-tools/ai-agentsread 2026-09-25