Machine Learning · head to head
Databricks vs Modal

Databricks
Machine Learning
Unified analytics platform for data engineering and data science
- From
- Free
- Rated
- -
The short version
- Each has a real cost: Databricks cloud compute is billed separately by the cloud provider on top of Databricks DBU charges; Modal the Team plan carries a $250 monthly base fee and returns only $100 of that as free credits, so $150 is a flat charge before any compute
- They diverge on capability: Databricks covers Delta Lake, Modal covers Serverless GPUs.
- Prices and features above were last checked on 30 August 2026.
Where they differ
Only the attributes on which Databricks and Modal actually diverge.
| Attribute | Databricks | Modal |
|---|---|---|
| Platforms | Web, Aws, Azure, Gcp | Cloud, Api |
| Category | Machine Learning | AI |
| Founded | 2013 | 2021 |
Identical on both: starting price (Free), pricing model (usage-based), 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 Databricks
- Delta Lake
- Apache Spark
- MLflow
- Unity Catalog
- Photon Engine
- Collaborative Notebooks
- AWS
- Azure
Only in Modal
- Serverless GPUs
- Python functions
- Fast cold starts
- Python SDK
- GitHub Actions
- Cloud storage
- Cloud support
- Api support
Both cover
- Auto-scaling
What people use each for
The jobs each tool is most often brought in to do.
Databricks
- Running Spark data engineering pipelines on managed clustersnot Modal
- Building a lakehouse over data in cloud object storagenot Modal
- Training and serving machine learning models alongside the datanot Modal
Modal
- Running serverless GPU workloads for model inference and trainingnot Databricks
- Executing Python functions on cloud compute without managing serversnot Databricks
Where each one falls short
Documented limitations, not opinions. Every one is a constraint you would hit in normal use.
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
Modal
- The Team plan carries a $250 monthly base fee and returns only $100 of that as free credits, so $150 is a flat charge before any compute
- Compute is billed per second across separate GPU and CPU meters, so total cost depends on execution time rather than any fixed rate
- The Starter plan's $30 monthly free credit is the only allowance below the paid base fee
- Enterprise volume discounts are custom and unpublished
Pricing, plan by plan
Databricks
Free- Community EditionFree
- Limited cluster
- Notebook environment
- Community support
- Standard$0.07/DBU
- Jobs compute
- SQL compute
- Standard support
Modal
Free- StarterFree
- 3 seats
- 100 containers
- 10 GPU concurrency
- Team$250/month
- Unlimited seats
- 5,000 containers
- 50 GPU concurrency
- Enterprise$null/custom
- Custom seats, containers, and GPU concurrency
Which should you pick?
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.
Choose Modal if
- You need serverless gpus.
- You want to start without paying.
- You work on Cloud, Api.
- You also want python functions.
Questions people ask
- Is Databricks or Modal better?
- Neither clearly leads. Databricks starts at Free and Modal at Free, and user ratings are close enough to be indistinguishable. Choose on capability and platform support.
- Which is cheaper, Databricks or Modal?
- Databricks starts at Free and Modal at Free.
- Does Databricks or Modal run on more platforms?
- Databricks runs on Web, Aws, Azure, Gcp. Modal runs on Cloud, Api.
- Can I use Databricks for free?
- Both have a free tier, so you can try either at no cost before committing.
- What is Databricks best used for?
- Databricks is most often used for running spark data engineering pipelines on managed clusters, building a lakehouse over data in cloud object storage, training and serving machine learning models alongside the data. Of those, running spark data engineering pipelines on managed clusters and building a lakehouse over data in cloud object storage are not what Modal is typically brought in for.
- What can Databricks do that Modal cannot?
- Databricks covers Delta Lake, Apache Spark, MLflow, Unity Catalog. Modal covers Serverless GPUs, Python functions, Fast cold starts, Python SDK. Both handle Auto-scaling.
Answered from the vendors’ own pages
Databricks: How is Databricks priced?
Databricks bills pay as you go with no up front cost, charging per second for the products used. Consumption is measured in Databricks Units, a normalised unit of processing power on the platform.
SourceModal: How much does Modal cost?
Modal uses pay-as-you-go pricing with Team plan at 250 USD/month base. Starter includes 30 USD/month free credits; Team includes 100 USD/month free credits. Compute charges per second for CPU cores, memory, and GPU instances.
SourceDatabricks: Does Databricks publish a per DBU price?
Not on its main pricing page. Rates vary by product and instance type, and Databricks directs buyers to individual product pricing pages and a calculator rather than listing a single figure.
SourceModal: Is there a free tier?
Yes, Starter plan is free plus 30 USD/month in compute credits included monthly for new users.
SourceDatabricks: Does the Databricks price include cloud costs?
No. Databricks states that if you configure it to work with your own cloud account, your cloud provider still charges you separately for the underlying resources.
SourceModal: What are the seat limits?
Starter plan includes 3 seats; Team plan provides unlimited seats; Enterprise tier has custom seat allocations.
SourceDatabricks: Can I get a discount on Databricks?
Databricks offers Committed Use Contracts, where larger usage commitments earn greater benefits, including options to use commitments flexibly across multiple clouds.
SourceRelated pages
Other head to heads
- Databricks vs AWS SageMaker
- Databricks vs Google Vertex AI
- Databricks vs Azure Machine Learning
- Databricks vs DataRobot
- Databricks vs TensorFlow
- Databricks vs SAS
- Databricks vs Snowflake
- Databricks vs Apache Spark MLlib
- Databricks vs Alteryx
- Databricks vs IBM SPSS
- Databricks vs Palantir Foundry
- Databricks vs BentoML
- Databricks vs ClearML
- Databricks vs Cohere
- Databricks vs Dask
- Databricks vs Fal AI
- Databricks vs BigQuery ML
- Databricks vs Pika
- Databricks vs Anthropic API
- Databricks vs D-ID
- Databricks vs Fathom
- Databricks vs RunPod
- Databricks vs Lambda Labs
- Databricks vs Banana
- Databricks vs CoreWeave
- Databricks vs Replicate
- Databricks vs LangGraph
- Databricks vs HeyGen
- Databricks vs Leonardo AI
- Databricks vs AI21 Labs
- Databricks vs Murf
- Databricks vs Pi
- Modal vs AWS SageMaker
- Modal vs Google Vertex AI
- Modal vs Azure Machine Learning
- Modal vs DataRobot
- Modal vs TensorFlow
- Modal vs SAS
- Modal vs Snowflake
- Modal vs Apache Spark MLlib
- Modal vs Alteryx
- Modal vs IBM SPSS
- Modal vs Palantir Foundry
- Modal vs BentoML
- Modal vs ClearML
- Modal vs Cohere
- Modal vs Dask
- Modal vs Fal AI
- Modal vs BigQuery ML
- Modal vs Pika
- Modal vs Anthropic API
- Modal vs D-ID
- Modal vs Fathom
- Modal vs RunPod
- Modal vs Lambda Labs
- Modal vs Banana
- Modal vs CoreWeave
- Modal vs Replicate
- Modal vs LangGraph
- Modal vs HeyGen
- Modal vs Leonardo AI
- Modal vs AI21 Labs
- Modal vs Murf
- Modal vs Pi

