Serverless compute vs Job cluster

[vaibhavaher2025]

Hi Guys,
For running the job with varying workload what should I use ? Serverless cluster or Job compute ?
What are positives and negatives?

(I'll be running my notebook from Azure data factory)

[MariuszK]

Hi
If you use PySpark for data processing than Job compute it has:
- lower cost
- support for PySpark
- flexible configuration
cons:
- Slower startup time

Serverless Warehouse:
- Faster startup time
- Dedicated for SQL
- Lower management
cons:
- not supporting PySpark
- more expensive for compute unit (Photon acceleration)
- less customization

[KaranamS]

It depends on cost, performance and startup time needed for your use-case.

Serverless compute is usually preferred choice because of its fast startup time and dynamic scaling. However, if your workload is long-running and predictable, job compute with auto scaling might be more cost-effective.