Is Unmeshed a good Astronomer alternative for workflow orchestration?

Yes. Unmeshed runs durable workflows with retries, scheduling, human approvals, role-based access control, and a full audit trail, with one flat price per execution. Workflows are defined in JSON, YAML, or code, with workers in Java, Go, TypeScript, or Python. Astronomer is managed Apache Airflow, and every workflow is a Python DAG.

How does Astronomer pricing compare to Unmeshed?

Unmeshed gives you 2,000 free executions a month, then a $20 a month Premium plan you can buy yourself, with prices on the pricing page. One workflow execution is one flat unit, however many steps run inside it. Astronomer pricing is usage-based. Team deployments start at $0.42 an hour, workers are billed separately, dedicated clusters start at $2.40 an hour, and higher plans are sold by quote.

Can I run data pipelines on Unmeshed instead of managed Airflow?

Yes. Unmeshed runs scheduled and event-driven pipelines with durable state, retries, cron scheduling down to one-minute intervals, and batch job scheduling. You can write pipeline steps in Python or any other supported language. Astro is built to run Airflow DAGs at scale, with data observability and dbt support through Cosmos, which is a real strength for data teams already on Airflow.

Can Unmeshed workflows use languages other than Python?

Yes. You can write Unmeshed workers in Java, Go, TypeScript, or Python and mix them in the same workflow, and you can define the workflow itself in JSON, YAML, or code. There is also a visual designer. Airflow workflows are written as Python DAGs, so teams that use other languages need a Python layer around them.

Do I have to rewrite my Airflow DAGs to migrate to Unmeshed?

No. You can keep your Python logic and call it from Unmeshed workers, so you get durable state, retries, and audit without rewriting the code inside your tasks. DAGs don't convert automatically, so most teams rebuild each one as an Unmeshed workflow and reuse the task code. Contact us if you want help scoping that.

Unmeshed

Astronomer

Astronomer alternatives where workflows aren't limited to Python DAGs.

Astro is managed Apache Airflow, so every workflow is a Python DAG. It bills deployments and workers separately by usage, with dedicated clusters, Astro Observe, and AI tokens on top, and most plans end in a quote.
Unmeshed counts one flat unit per workflow execution, however many steps run inside it. You define workflows in JSON, YAML, or code, with workers in Java, Go, TypeScript, or Python, and the same engine runs your pipelines, APIs, approvals, and agents.

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Overview

Two ways to run a workflow.

About Unmeshed

Unmeshed is a workflow orchestration platform built by the team behind Netflix Conductor. You define workflows in JSON or YAML, with code-based workers in Java, Go, TypeScript, or Python. Agents run as steps next to plain code, API calls, and human approvals, and the engine keeps state, retries failed steps, and records every run.

About Astronomer

Astronomer builds Astro, a fully managed orchestration platform powered by Apache Airflow. You write Python DAGs, and Astro runs them with its own scheduler and runtime, plus observability, an Astro CLI, Cosmos for dbt, and Otto, an AI agent for Airflow. Astro Private Cloud runs the same platform in your own environment.

Comparison

Unmeshed vs Astronomer.

	Unmeshed	Astronomer
Platform
Built for	Workflows, APIs, batch jobs, and AI agents	Data, ML, and AI pipelines on Airflow
Workflow definitions	JSON, YAML, or code	Python DAGs
Worker languages	Java, Go, TypeScript, Python	Python
Visual designer	Included
Resiliency and operations
Cron and event scheduling	Included	Included
Built-in retries and error handling	Included	Included
Human-in-the-loop approvals	Included
Data observability and lineage		Included
Pricing
Pricing model	Flat, one unit per workflow execution	Usage-based, deployments and workers metered separately
Billed across multiple meters	Not included	Included
Free tier	2,000 workflow executions a month	Free trial
Upgrade without a sales call	Included
Security, compliance, and governance
Role-based access control	Included
SSO / SAML		Included
Audit logs	Included	Included
Self-hosted / on-premises deployment	Included

Workflows in more than Python.

Build pipelines, APIs, approvals, and agents in one engine, on a free tier you sign up for yourself.

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Pricing

Astronomer pricing runs on meters. Ours is one number.

Astro pricing is usage-based. Deployments and workers are billed separately, dedicated clusters cost extra, and Astro Observe and AI token usage add more. Team deployments start at $0.42 an hour, and the higher plans come as a quote. Unmeshed lists three plans with prices on the page and counts one flat unit, a workflow execution, no matter how many steps run inside it. You can move from free to paid yourself.

Free forever

For solo builders exploring workflow orchestration.

$0/month

No credit card required

Get Started Free

2,000 workflow executions / month
Unlimited steps per workflow
Community support

Premium

For individuals and small teams ready to orchestrate at scale.

$20/month

Billed monthly, annual saves 2 months

Get Started

10,000 workflow executions / month
Batch job scheduling
Email support

Enterprise

For organizations with scale, compliance, and infrastructure requirements.

Custom pricing

Tailored to your scale and compliance requirements

Contact Sales

Unlimited executions, workflows & seats
SSO / SAML and RBAC
Dedicated support with SLAs

Astronomer pricing, for reference

See Astronomer pricing

Deployments and workers

Team deployments start at $0.42 an hour, roughly $300 a month for a deployment that runs around the clock, before workers. Workers are billed separately.

Clusters and add-ons

Standard multi-tenant clusters are included. Dedicated clusters start at $2.40 an hour. Astro Observe and AI token usage cost extra.

Plans and governance

Team adds high availability and 7-day audit logs. Business adds SSO enforcement and 90-day audit logs. Enterprise adds custom RBAC, SCIM, and remote execution agents.

Also sold through the AWS, Azure, and Google Cloud marketplaces. Pricing details change often; confirm current numbers on Astronomer's site.

Agentic AI

Agents and pipelines in one place

Astronomer

Astronomer supports AI workflows on Airflow and offers Otto, an agent that writes DAGs, investigates failures, and plans upgrades. It is a strong fit if your team lives in Airflow and wants AI help with the pipelines themselves.

Unmeshed

Unmeshed runs agents as steps inside the same durable workflow as your pipelines, APIs, decisions, and human approvals, and works with MCP tools natively. The agent is part of the workflow, not a tool for writing it.

Cost and infrastructure

Managed Airflow bills the runtime. Unmeshed bills the workflow.

Astronomer

Astro removes the work of running Airflow yourself, which is the reason to buy it. The bill follows the infrastructure behind it, with deployment hours, workers, and clusters each metered. Running it in your own environment is Astro Private Cloud, a separate deployment option.

Unmeshed

Unmeshed self-hosts the whole platform on your own VM or Kubernetes cluster, or you can use Unmeshed Cloud, and you choose without a sales call first.

Feature comparison

Astronomer makes you plan for this. Unmeshed already did.

The stuff you won't have to build yourself.

Pricing predictability

One number, not a meter for each resource.

Unmeshed

Workflow executions are counted flat, no matter how many steps, workers, or clusters a workflow uses.

Astronomer

Deployments and workers are billed separately, with dedicated clusters, Astro Observe, and AI tokens on top.

Workflow definitions

Define it your way, not only in Python.

Unmeshed

Workflows are defined in JSON, YAML, or code, with workers in Java, Go, TypeScript, or Python.

Astronomer

Workflows are Python DAGs, so every change goes through a Python developer.

Governance

Access control before the Enterprise deal.

Unmeshed

Role-based access control is available as a baseline platform capability, not held for a custom conversation.

Astronomer

SSO enforcement arrives on Business, and custom RBAC and SCIM are Enterprise features.

Workflow scope

Pipelines are one use case, not the whole product.

Unmeshed

The same engine runs pipelines, APIs, batch jobs, approvals, and agents with the same durable state.

Astronomer

The platform is built around Airflow data and AI pipelines, so other process types need other tools.

Developer experience

Plain functions. Any language.

Workers are plain functions. Register them, start a process, and the platform handles state and retries. Write them in Python, TypeScript, Java, or Go.

Retries, state, and scheduling come built in, so there's no extra worker setup to hand roll.

Explore the SDKs Read the docs

worker.py

from unmeshed.sdk.configs.client_config import ClientConfig
from unmeshed.sdk.unmeshed_client import UnmeshedClient
from unmeshed.sdk.decorators.worker_function import worker_function

client_config = ClientConfig()
client_config.set_client_id("your-client-id")
client_config.set_auth_token("your-auth-token")
client = UnmeshedClient(client_config)

@worker_function(name="charge-order", namespace="default", max_in_progress=100)
def charge_order(input: OrderInput) -> ChargeResult:
    # your business logic — the engine handles
    # state, retries, and observability
    return charge_card(input)

client.start()

Frequently asked questions

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