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Databases · head to head

Apache Airflow vs Memcached

Apache Airflow logo

Apache Airflow

Databases

Programmatically author, schedule and monitor data workflows in Python

From
Free
Rated
-
Full reviewWebsite
Memcached logo

Memcached

Databases

Distributed memory object caching system

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; Memcached no persistence at all: restart a node and its cache is gone, which every design must assume
  • They diverge on capability: Apache Airflow covers Pipelines as Python, Memcached covers In-memory key-value cache.

Where they differ

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

Attributes where Apache Airflow and Memcached differ
AttributeApache AirflowMemcached
Pricing modelOpen source, no licence fee; managed services billed separatelyOpen source, no licence fee; managed cloud billed separately
PlatformsLinux, Docker, Kubernetes, Self-hostedLinux, macOS, Windows, Docker, Self-hosted

Identical on both: starting price (Free), free tier (Yes), 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 Memcached

  • In-memory key-value cache
  • Multithreaded
  • Client-side sharding
  • Predictable memory use

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

Memcached

  • Caching expensive database query results to cut loadnot Apache Airflow
  • Session storage where losing sessions on restart is acceptablenot Apache Airflow
  • Fronting an API whose responses are costly and change slowlynot 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

Memcached

  • No persistence at all: restart a node and its cache is gone, which every design must assume
  • No replication or failover, so losing a node loses that share of the cache
  • Only simple key-value, with none of the lists, sorted sets or streams Redis offers
  • Values are capped at 1MB by default, which surprises teams caching large documents

Pricing, plan by plan

Apache Airflow

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

Memcached

Free
  • MemcachedFree
    • Full functionality
    • Self-hosted
    • No usage limits

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 Memcached if

  • You need in-memory key-value cache.
  • You want to start without paying.
  • You work on Linux, macOS, Windows, Docker, Self-hosted.
  • You also want multithreaded.
Memcached review

Questions people ask

Is Apache Airflow or Memcached better?
Neither clearly leads. Apache Airflow starts at Free and Memcached at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Airflow or Memcached?
Apache Airflow starts at Free and Memcached at Free.
Does Apache Airflow or Memcached run on more platforms?
Apache Airflow runs on Linux, Docker, Kubernetes, Self-hosted. Memcached runs on Linux, macOS, Windows, Docker, Self-hosted.
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 Memcached is typically brought in for.
What can Apache Airflow do that Memcached cannot?
Apache Airflow covers Pipelines as Python, Web UI, Cloud provider packages, Jinja templating. Memcached covers In-memory key-value cache, Multithreaded, Client-side sharding, Predictable memory use.

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.

Memcached: Is Memcached free?

Yes, open source with no licence fee.

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.

Memcached: Memcached or Redis?

Memcached is a pure cache: simpler, multithreaded and very predictable. Redis adds persistence, replication and rich data structures, which is why it is the default choice unless you specifically want a cache and nothing more.

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.

Memcached: Does Memcached persist data?

No. Everything is in memory and lost on restart, by design.

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.

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