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Databases · head to head

Apache Airflow vs Milvus

Apache Airflow logo

Apache Airflow

Databases

Programmatically author, schedule and monitor data workflows in Python

From
Free
Rated
-
Full reviewWebsite
Milvus logo

Milvus

Machine Learning

Open-source vector database for scalable similarity search

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; Milvus vector dimensions are capped at 32,768
  • They diverge on capability: Apache Airflow covers Pipelines as Python, Milvus covers Billion-scale vectors.
  • Prices and features above were last checked on 30 August 2026.

Where they differ

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

Attributes where Apache Airflow and Milvus differ
AttributeApache AirflowMilvus
Pricing modelOpen source, no licence fee; managed services billed separatelyfreemium
PlatformsLinux, Docker, Kubernetes, Self-hostedLinux, Mac, Windows, Web
CategoryDatabasesMachine Learning
FoundedUnknown2017

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 Milvus

  • Billion-scale vectors
  • Multiple index types
  • GPU acceleration
  • Hybrid search
  • Data partitioning
  • PyTorch
  • TensorFlow
  • Hugging Face

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

Milvus

  • Self hosting a vector database for semantic searchnot Apache Airflow
  • Storing and querying embeddings for retrieval augmented generationnot Apache Airflow
  • Similarity search over images, audio or text at scalenot 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

Milvus

  • Vector dimensions are capped at 32,768
  • A collection is limited to 64 fields, 1,024 partitions and 16 shards
  • Only 1 index is allowed per field
  • Search returns at most 16,384 vectors as top-k, and nq is capped at 16,384
  • Input and output per RPC is capped at 64 MB for insert, search and query
  • VARCHAR values are limited to 65,535 characters
  • Data loaded into query nodes cannot exceed 90% of available memory
  • An instance supports at most 65,536 collections

Pricing, plan by plan

Apache Airflow

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

Milvus

Free
  • Open SourceFree
    • Full features
    • Self-hosted
    • Community support
  • Zilliz CloudFree
    • Managed service
    • Free tier available

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 Milvus if

  • You need billion-scale vectors.
  • You want to start without paying.
  • You work on Linux, Mac, Windows, Web.
  • You also want multiple index types.
Milvus review

Questions people ask

Is Apache Airflow or Milvus better?
Neither clearly leads. Apache Airflow starts at Free and Milvus at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Airflow or Milvus?
Apache Airflow starts at Free and Milvus at Free.
Does Apache Airflow or Milvus run on more platforms?
Apache Airflow runs on Linux, Docker, Kubernetes, Self-hosted. Milvus runs on Linux, Mac, Windows, Web.
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 Milvus is typically brought in for.
What can Apache Airflow do that Milvus cannot?
Apache Airflow covers Pipelines as Python, Web UI, Cloud provider packages, Jinja templating. Milvus covers Billion-scale vectors, Multiple index types, GPU acceleration, Hybrid search.

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.

Milvus: How much does Milvus cost?

Milvus is open-source and free to use and modify. The self-hosted version has no licensing cost. Zilliz Cloud (the managed SaaS version) does not publish pricing on the website.

Source
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.

Milvus: Is there a free or open-source version of Milvus?

Yes, Milvus is fully open-source and available for free. Milvus Lite is a lightweight option for learning and prototyping that can be installed via pip.

Source
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.

Milvus: Does Milvus offer a managed cloud service?

Yes, Zilliz Cloud is a fully managed Milvus cloud offering with serverless and dedicated cluster options. Pricing must be requested from the company as it is not listed on the public website.

Source
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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