Software · head to head
Ollama vs Databricks

Ollama
Software
Open-source tool for running LLMs locally on desktop and servers
- From
- Free
- Rated
- -

Databricks
Software
Unified analytics platform for data engineering and data science
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Ollama requires user to provide computational hardware; no free cloud compute; models may not fit in available RAM on typical machines; Databricks cloud compute is billed separately by the cloud provider on top of Databricks DBU charges
Where they differ
Only the attributes on which Ollama and Databricks actually diverge.
| Attribute | Ollama | Databricks |
|---|---|---|
| Pricing model | open-source | usage-based |
| Platforms | macOS, Windows, Linux, Cloud (AWS, Google Cloud, Azure, self-hosted) | Web, Aws, Azure, Gcp |
| Founded | Unknown | 2013 |
Identical on both: starting price (Free), free tier (Yes), user rating (Not yet rated), category (Unknown).
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 Ollama
Nothing recorded that Databricks does not also cover.
Only in Databricks
- Delta Lake
- Apache Spark
- MLflow
- Unity Catalog
- Photon Engine
- Collaborative Notebooks
- Auto-scaling
- AWS
What people use each for
The jobs each tool is most often brought in to do.
Ollama
- Local development and testing without API costs or rate limitsnot Databricks
- Privacy-sensitive applications requiring data to remain on-devicenot Databricks
- Cost-sensitive deployments where computational resources are already availablenot Databricks
- Fully offline environments or air-gapped networksnot Databricks
Databricks
- Running Spark data engineering pipelines on managed clustersnot Ollama
- Building a lakehouse over data in cloud object storagenot Ollama
- Training and serving machine learning models alongside the datanot Ollama
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
Ollama
- Requires user to provide computational hardware; no free cloud compute; models may not fit in available RAM on typical machines
- No hosted service option for inference; all computational burden falls to user
- Limited to open-weight models; cannot run proprietary models like GPT-4 or Claude locally
- Performance depends entirely on user's hardware; no SLAs or guarantees on speed
Databricks
- Cloud compute is billed separately by the cloud provider on top of Databricks DBU charges
- The free trial lasts 14 days
- Discounts require a Committed Use Contract, with larger commitments needed for larger discounts
- Azure Databricks pricing is set by Microsoft rather than by Databricks
- Security and compliance capabilities are sold as separate platform add ons rather than included in the base rate
Pricing, plan by plan
Ollama
FreeNo published plan breakdown. See the Ollama review.
Databricks
Free- Community EditionFree
- Limited cluster
- Notebook environment
- Community support
- Standard$0.07/DBU
- Jobs compute
- SQL compute
- Standard support
Which should you pick?
Choose Ollama if
- You want to start without paying.
- You work on macOS, Windows, Linux, Cloud (AWS, Google Cloud, Azure, self-hosted).
Choose Databricks if
- You need delta lake.
- You want to start without paying.
- You work on Web, Aws, Azure, Gcp.
- You also want apache spark.
Questions people ask
- Is Ollama or Databricks better?
- Neither clearly leads. Ollama starts at Free and Databricks at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Ollama or Databricks?
- Ollama starts at Free and Databricks at Free.
- Does Ollama or Databricks run on more platforms?
- Ollama runs on macOS, Windows, Linux, Cloud (AWS, Google Cloud, Azure, self-hosted). Databricks runs on Web, Aws, Azure, Gcp.
- Can I use Ollama for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Ollama best used for?
- Ollama is most often used for local development and testing without api costs or rate limits, privacy-sensitive applications requiring data to remain on-device, cost-sensitive deployments where computational resources are already available, fully offline environments or air-gapped networks. Of those, local development and testing without api costs or rate limits and privacy-sensitive applications requiring data to remain on-device are not what Databricks is typically brought in for.
- What can Ollama do that Databricks cannot?
- Databricks covers Delta Lake, Apache Spark, MLflow, Unity Catalog.
Related pages
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