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Databases · head to head

Apache Airflow vs Soketi

Apache Airflow logo

Apache Airflow

Databases

Programmatically author, schedule and monitor data workflows in Python

From
Free
Rated
-
Full reviewWebsite
Soketi logo

Soketi

Developer Tools

Self-hosted, Pusher-compatible WebSockets server with a stalled maintenance record

From
Free
Rated
-
Full reviewWebsite

The short version

  • Each has a real cost: Apache Airflow self-hosting is genuinely heavy: scheduler, metadata database, workers and executor choice are a standing operational job; Soketi maintenance has effectively stalled: the maintainer has said time is severely limited, releases are infrequent, and the community has been discussing whether the project is abandoned, which means security fixes may not arrive.
  • They diverge on capability: Apache Airflow covers Pipelines as Python, Soketi covers Pusher protocol compatibility.
  • Prices and features above were last checked on 31 August 2026.

Where they differ

Only the attributes on which Apache Airflow and Soketi actually diverge.

Attributes where Apache Airflow and Soketi differ
AttributeApache AirflowSoketi
Pricing modelOpen source, no licence fee; managed services billed separatelyOpen source, no licence fee
PlatformsLinux, Docker, Kubernetes, Self-hostedLinux, macOS, Windows
CategoryDatabasesDeveloper Tools

Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated).

What each one covers

Drawn from each product's published feature list. An absence here means we hold no record of it - not that the product lacks it.

Only in Apache Airflow

  • Pipelines as Python
  • Web UI
  • Cloud provider packages
  • Jinja templating
  • Retries and dependencies
  • Extensible operators

Only in Soketi

  • Pusher protocol compatibility
  • Presence and private channels
  • Horizontal scaling
  • App management backends
  • Webhooks
  • Prometheus metrics

What people use each for

The jobs each tool is most often brought in to do.

Apache Airflow

  • Scheduling nightly ETL where step order and retries matternot Soketi
  • Coordinating machine learning training and evaluation runsnot Soketi
  • Orchestrating dbt runs alongside extraction and loadingnot Soketi
  • Replacing a sprawl of cron jobs with dependencies and visible run historynot Soketi

Soketi

  • A Laravel application that already uses Echo and wants to stop paying a hosted realtime providernot Apache Airflow
  • Realtime notifications or presence indicators where data must not leave your own infrastructure for compliance reasonsnot Apache Airflow
  • A local or CI environment that needs a Pusher-compatible server without hitting a paid accountnot Apache Airflow
  • A high-connection-count application where hosted per-connection pricing has become the largest line in the infrastructure billnot Apache Airflow

Where each one falls short

Documented limitations, not opinions. Every one is a constraint you would hit in normal use.

Apache Airflow

  • Self-hosting is genuinely heavy: scheduler, metadata database, workers and executor choice are a standing operational job
  • Built for scheduled batch work, and a poor fit for event-driven or sub-minute latency pipelines
  • Because DAGs are Python that the scheduler parses continuously, expensive top-level code in a DAG file slows the whole scheduler
  • Local development and testing of DAGs is awkward compared with newer orchestrators designed with it in mind

Soketi

  • Maintenance has effectively stalled: the maintainer has said time is severely limited, releases are infrequent, and the community has been discussing whether the project is abandoned, which means security fixes may not arrive.
  • Dependency drift on Node and uWebSockets.js will eventually force you to fork or migrate, and that cost is unbudgeted at the point you adopt it.
  • There is no commercial support to buy, so a production incident at three in the morning is entirely your problem with no escalation path.
  • Scaling beyond a single node needs Redis and careful configuration, and getting presence channels correct across nodes is a genuine source of subtle bugs.
  • It implements the Pusher protocol rather than tracking it, so any protocol feature Pusher adds later will not appear, and the compatibility guarantee slowly decays.

Pricing, plan by plan

Apache Airflow

Free
  • Apache AirflowFree
    • Full scheduler and web UI
    • All provider packages
    • No task or DAG limits

Soketi

Free
  • SoketiFree
    • MIT licensed
    • Unlimited connections subject to your own hardware
    • No vendor billing

Which should you pick?

Choose Apache Airflow if

  • You need pipelines as python.
  • You want to start without paying.
  • You work on Linux, Docker, Kubernetes, Self-hosted.
  • You also want web ui.
Apache Airflow review

Choose Soketi if

  • You need pusher protocol compatibility.
  • You want to start without paying.
  • You work on Linux, macOS, Windows.
  • You also want presence and private channels.
Soketi review

Questions people ask

Is Apache Airflow or Soketi better?
Neither clearly leads. Apache Airflow starts at Free and Soketi at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Airflow or Soketi?
Apache Airflow starts at Free and Soketi at Free.
Does Apache Airflow or Soketi run on more platforms?
Apache Airflow runs on Linux, Docker, Kubernetes, Self-hosted. Soketi runs on Linux, macOS, Windows.
Can I use Apache Airflow for free?
Both have a free tier, so you can try either at no cost before committing.
What is Apache Airflow best used for?
Apache Airflow is most often used for scheduling nightly etl where step order and retries matter, coordinating machine learning training and evaluation runs, orchestrating dbt runs alongside extraction and loading, replacing a sprawl of cron jobs with dependencies and visible run history. Of those, scheduling nightly etl where step order and retries matter and coordinating machine learning training and evaluation runs are not what Soketi is typically brought in for.
What can Apache Airflow do that Soketi cannot?
Apache Airflow covers Pipelines as Python, Web UI, Cloud provider packages, Jinja templating. Soketi covers Pusher protocol compatibility, Presence and private channels, Horizontal scaling, App management backends.

Answered from the vendors’ own pages

Apache Airflow: Is Apache Airflow free?

Yes. Airflow is open source under the Apache Software Foundation with no licence fee. Costs are the infrastructure to run it, or a managed service such as Google Cloud Composer or Amazon MWAA.

Soketi: Is Soketi still maintained?

Barely. The maintainer has stated that available time is very limited and releases have been sparse; treat it as community-maintained.

Apache Airflow: What language are Airflow workflows written in?

Python. A workflow is a Python file, so standard language features including loops and datetime handling can generate tasks dynamically, with no XML or command-line configuration.

Soketi: Do I need to change my client code?

No. Pusher client SDKs and Laravel Echo work by changing the host, port and credentials.

Apache Airflow: Is Airflow suitable for real-time pipelines?

Not really. Airflow is designed for scheduled batch orchestration. Event-driven or sub-minute work is better served by a streaming platform such as Kafka or a purpose-built streaming engine.

Soketi: What does it cost?

Nothing in licence fees. It is MIT licensed; you pay for the server it runs on.

Apache Airflow: What are the main alternatives to Airflow?

Dagster and Prefect are the two most commonly weighed against it, both newer and both designed around the local development and testing experience Airflow is criticised for.

Soketi: What are people moving to?

Laravel Reverb for Laravel applications, and Sockudo, a Rust reimplementation, for others.

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