Databricks suits data teams that want an open lakehouse for data engineering, machine learning, AI agents and BI on any cloud, with governance through Unity Catalog. Snowflake suits teams that want a fully managed data platform where analysts can query and share data without running infrastructure, with Cortex AI built in. If your work is engineering and AI heavy, start with Databricks; if it's SQL analytics and data sharing, start with Snowflake.
Both now pitch themselves as data and AI platforms, and they often share a shortlist. I read Databricks' home, platform and try-for-free pages, and Snowflake's platform page and its trial account documentation.
Databricks and Snowflake compared
| Databricks | Snowflake | |
|---|---|---|
| Core idea | Open lakehouse for data and AI | Fully managed data and AI platform |
| Governance | Unity Catalog | Horizon Catalog |
| AI features | Agents, AI/BI, model building | Cortex AI |
| Open formats | Built on open source technologies | Read and write access for Iceberg tables |
| Trial | Two weeks of full platform access | 30 days or until free usage runs out |
| Ongoing free option | Free Edition for non-commercial learning | Not on the pages I read |
| Clouds | Any cloud | Across clouds and regions |
Read the free-option small print first
Both trials hide rules worth knowing. Databricks' Free Edition has no expiry and needs no cloud account, but it's for personal, non-commercial learning, and Databricks' own comparison table says it reserves the right to train on your data in that edition. For business evaluation it points you to a two-week trial on a work email instead.
Snowflake's docs say a trial needs only an email address and no payment details, but AI features stay switched off on self-service trials until you add a card. The trial runs 30 days or until you've used your free usage balance, and at the end the account is suspended and any unused balance expires.
What Databricks does well
Databricks is built for engineering-led teams. One platform covers data engineering pipelines, data warehousing, business intelligence, governance and AI, so the same team can clean data, train models and ship agents. Its pitch is openness: it runs on any cloud and is built on open source technologies, which matters if you don't want your data locked into one format.
What Snowflake does well
Snowflake takes infrastructure off your plate. It's a single, fully managed platform, its Adaptive Compute picks right-sized compute and routes queries automatically, and it now offers Snowflake Postgres and Openflow alongside Cortex AI. Teams that share data across business units or partners get an interoperable setup across clouds and regions.
A wider shortlist is in data warehouse tools.
Questions for your data team
- Is most of your work SQL analytics, or data engineering and machine learning?
- Do you want to manage compute settings, or have them chosen for you?
- Do you rely on open table formats like Iceberg?
- Which cloud and region must your data live in?
- Will you test AI features during the trial?
If you're earlier in the journey, my round-up of data analytics tools covers simpler options, and this guide to Power BI data governance shows how governance works on the reporting side.
Picking a cloud and region
Snowflake's trial docs say the cloud platform, region and edition you choose at sign-up can affect how quickly you use your free balance, because some Enterprise features use more. Databricks' trial page says its trial works with any data on any cloud and lets you connect your own data securely for a proof of concept.
Messy source records are the usual problem, covered in master data management software.
My advice on Databricks or Snowflake
If your team writes pipelines and builds models, trial Databricks on a work email and load real data in week one, because the trial is only two weeks. If your team lives in SQL and wants less to manage, trial Snowflake, add a card early if you want to test Cortex AI, and pick your cloud and region carefully because they shape how fast the free balance goes.
Want AI doing the heavy lifting in your marketing?
I build the systems that handle the boring 80 percent, so you get your week back. Done properly, with the human kept in.
Do you make data platform or analytics software? Tool makers can ask to be considered for a featured place in comparisons like this one.
Frequently asked questions
Is Databricks or Snowflake better for AI?
Both now sell AI features. Databricks covers data engineering, model building and agents on a lakehouse; Snowflake offers Cortex AI inside a fully managed platform.
How long is the Snowflake free trial?
Snowflake's docs say 30 days from sign-up or until you've used the free usage balance, whichever comes first.
Does Snowflake need a card for its trial?
No payment details are needed to sign up, but Snowflake says AI features stay disabled on self-service trials until you add a card.
Is Databricks free?
Databricks offers a Free Edition for personal, non-commercial learning with no expiry, and a two-week trial for business evaluation.
Does Databricks train on Free Edition data?
Databricks' comparison table says it reserves the right to train on your data in Free Edition.
What happens when a Snowflake trial ends?
The account is suspended and any unused free balance expires. You can still log in, but you can't run queries until you upgrade.
Which clouds do Databricks and Snowflake run on?
Databricks says its trial works on any cloud. Snowflake asks you to choose a cloud platform and region when you sign up.
