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Databases · head to head

Apache Airflow vs SurrealDB

Apache Airflow logo

Apache Airflow

Databases

Programmatically author, schedule and monitor data workflows in Python

From
Free
Rated
-
Full reviewWebsite
SurrealDB logo

SurrealDB

Databases

Multi-model database combining documents, graphs, vectors and time-series

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; SurrealDB the listed $0.192/node/hr Scale pricing lacks transparent higher-tier rates, requiring a sales conversation for full production sizing.
  • They diverge on capability: Apache Airflow covers Pipelines as Python, SurrealDB covers Multi-model engine.
  • Prices and features above were last checked on 29 August 2026.

Where they differ

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

Attributes where Apache Airflow and SurrealDB differ
AttributeApache AirflowSurrealDB
Pricing modelOpen source, no licence fee; managed services billed separatelyusage-based
PlatformsLinux, Docker, Kubernetes, Self-hostedweb, api, windows, mac, linux
FoundedUnknown2022

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 SurrealDB

  • Multi-model engine
  • ACID transactions
  • Hybrid retrieval
  • Horizontal scaling
  • Multi-region disaster recovery
  • FIPS-compliant cryptography

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

SurrealDB

  • AI agent memory and retrieval-augmented generationnot Apache Airflow
  • Applications needing documents, graphs and vectors in one databasenot Apache Airflow
  • Knowledge graph construction from unstructured datanot Apache Airflow
  • Regulated workloads requiring SOC2/ISO27001/HIPAA-eligible hostingnot 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

SurrealDB

  • The listed $0.192/node/hr Scale pricing lacks transparent higher-tier rates, requiring a sales conversation for full production sizing.
  • As a newer multi-model database, it has a smaller ecosystem of drivers, ORMs and community tooling than established single-model databases.
  • HIPAA compliance is only available as an Enterprise add-on rather than included in standard paid tiers.
  • Combining multiple data models in one engine can add query-planning complexity compared to purpose-built single-model databases.

Pricing, plan by plan

Apache Airflow

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

SurrealDB

Free
  • StartFree
    • 1 free instance, then from $0.021/hr
    • 1GB storage free forever
    • Vertical scaling to terabytes
  • Scale$0.192/month
    • $0.192/node/hr
    • Production-grade fault tolerance
    • Horizontal scaling to petabytes
  • Enterprise$undefined/month
    • Self-hosted, custom pricing
    • Clustered fault-tolerant deployments
    • FIPS-compliant cryptography

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 SurrealDB if

  • You need multi-model engine.
  • You want to start without paying.
  • You work on web, api, windows, mac, linux.
  • You also want acid transactions.
SurrealDB review

Questions people ask

Is Apache Airflow or SurrealDB better?
Neither clearly leads. Apache Airflow starts at Free and SurrealDB at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
Which is cheaper, Apache Airflow or SurrealDB?
Apache Airflow starts at Free and SurrealDB at Free.
Does Apache Airflow or SurrealDB run on more platforms?
Apache Airflow runs on Linux, Docker, Kubernetes, Self-hosted. SurrealDB runs on web, api, windows, mac, linux.
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 SurrealDB is typically brought in for.
What can Apache Airflow do that SurrealDB cannot?
Apache Airflow covers Pipelines as Python, Web UI, Cloud provider packages, Jinja templating. SurrealDB covers Multi-model engine, ACID transactions, Hybrid retrieval, Horizontal scaling.

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.

SurrealDB: What does SurrealDB cost?

SurrealDB Cloud's Start plan is free with one free instance (then from $0.021/hr), the Scale plan runs $0.192/node/hr for production workloads, and Enterprise self-hosted deployments use custom pricing.

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.

SurrealDB: Is there a free plan and what are its limits?

Yes, the Start plan includes one free instance with 1GB of storage free forever and 1GB of outbound data transfer per month, aimed at prototypes and development.

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.

SurrealDB: How is billing handled?

Customers are invoiced monthly based on actual usage in a pay-as-you-go model with no long-term commitments, though commitment-based discounts are available.

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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