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Databases · head to head

Apache Airflow vs Knack

Apache Airflow logo

Apache Airflow

Databases

Programmatically author, schedule and monitor data workflows in Python

From
Free
Rated
-
Full reviewWebsite
Knack logo

Knack

Databases

Hosted no-code database and web app builder priced by stored records and storage, with unlimited user accounts on every plan.

From
$59/month
Rated
-
Full reviewWebsite

The short version

  • Only Apache Airflow has a free tier, so it costs nothing to try first.
  • Each has a real cost: Apache Airflow self-hosting is genuinely heavy: scheduler, metadata database, workers and executor choice are a standing operational job; Knack plans are capped by stored records, so an application that logs events or keeps history rather than current state climbs tiers on data volume alone, and archiving old records becomes a permanent maintenance chore rather than a one-off.
  • They diverge on capability: Apache Airflow covers Pipelines as Python, Knack covers Visual database builder.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

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

Attributes where Apache Airflow and Knack differ
AttributeApache AirflowKnack
Starting priceFree$59/month
Pricing modelOpen source, no licence fee; managed services billed separatelysubscription
Free tierYesNo
PlatformsLinux, Docker, Kubernetes, Self-hostedWeb

Identical on both: user rating (Not yet rated), category (Databases).

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 Knack

  • Visual database builder
  • User logins and roles
  • Page builder
  • Unlimited users
  • E-commerce
  • Automation flows
  • Scheduled tasks
  • REST API and webhooks

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 Knack
  • Coordinating machine learning training and evaluation runsnot Knack
  • Orchestrating dbt runs alongside extraction and loadingnot Knack
  • Replacing a sprawl of cron jobs with dependencies and visible run historynot Knack

Knack

  • A member or client portal where thousands of external people need their own login and see only their own recordsnot Apache Airflow
  • Replacing a shared spreadsheet used by a team that has outgrown it but cannot justify a developer to build a bespoke internal toolnot Apache Airflow
  • Inventory, asset or case tracking for a small operations team that needs roles, forms and a record of who changed whatnot Apache Airflow
  • A registration or booking application for an association, school or non-profit where the user count is large and the record count stays modestnot 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

Knack

  • Plans are capped by stored records, so an application that logs events or keeps history rather than current state climbs tiers on data volume alone, and archiving old records becomes a permanent maintenance chore rather than a one-off.
  • API access is capped per day, at 1,000 calls on the entry plan and 10,000 at the Corporate tier, so a scheduled sync or a busy automation can exhaust the day's quota before the working day ends and integrations then fail silently.
  • The application itself cannot be exported or self-hosted; records can be downloaded but the pages, roles, flows and business logic exist only inside Knack, so outgrowing the platform means rebuilding the app rather than moving it.
  • Customisation beyond the builder is limited to injected CSS and JavaScript that Knack's support does not cover, so any non-standard interface behaviour becomes yours to maintain against a DOM the vendor can change without warning.
  • Compliance capabilities that regulated buyers assume are baseline, HIPAA and GovCloud options, advanced SSO, IP restrictions and private environments, are gated to the Corporate and Enterprise tiers, so a small regulated pilot cannot legitimately start on an entry plan.

Pricing, plan by plan

Apache Airflow

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

Knack

$59/month
  • Starter$59/month
    • 20,000 database records
    • Unlimited users, tables, fields
    • 25 AI credits
  • Pro$130/month
    • 50,000 database records
    • Remove Knack branding
    • E-commerce payments
  • Corporate$300/month
    • 125,000-2.5M database records
    • App restore functionality
    • Advanced SSO
  • Enterprise$null/month
    • Dedicated account manager
    • HIPAA/GovCloud-based options
    • Custom pricing

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 Knack if

  • You need visual database builder.
  • You also want user logins and roles.
Knack review

Questions people ask

Is Apache Airflow or Knack better?
Neither clearly leads. Apache Airflow starts at Free and Knack at $59/month, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Airflow or Knack?
Apache Airflow has a free tier; the other does not. Paid plans start at Free for Apache Airflow and $59/month for Knack.
Does Apache Airflow or Knack run on more platforms?
Apache Airflow runs on Linux, Docker, Kubernetes, Self-hosted. Knack runs on Web.
Can I use Apache Airflow for free?
Yes. Apache Airflow has a free tier, so you can try it without paying. Knack starts at $59/month.
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 Knack is typically brought in for.
What can Apache Airflow do that Knack cannot?
Apache Airflow covers Pipelines as Python, Web UI, Cloud provider packages, Jinja templating. Knack covers Visual database builder, User logins and roles, Page builder, Unlimited users.

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.

Knack: Is Knack charged per user?

No. User accounts are unlimited on all plans. Plans are bounded by stored record count, file storage, API calls per day and automation transactions.

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.

Knack: What happens when I exceed the record limit?

You move to a higher tier or reduce stored records. Because the limit is on data rather than people, apps that accumulate history hit it while apps that track a fixed set of entities generally do not.

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.

Knack: Can I export my application or self-host it?

You can export record data. The application itself, its pages, roles, permissions and flows, is not exportable and cannot be self-hosted, so leaving means rebuilding elsewhere.

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.

Knack: Is it suitable for public-facing portals?

That is its strongest case, because logins are unlimited and role-based permissions are built in. The constraint is record volume and API throughput, not audience size.

Knack: Can I use it for regulated data?

HIPAA-aligned and government cloud options exist but only on the Enterprise tier, along with private server environments. Lower tiers should not be used for regulated workloads.

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