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Databricks
✔ Verified Freemium
👁 125
Lakehouse platform for data engineering, analytics, machine learning, MLOps and generative AI workloads.
Databricks combines data engineering, analytics, machine learning and AI development on a lakehouse architecture. Organizations use it to process large datasets, build data pipelines, run SQL analytics, train and deploy machine learning models and develop generative AI applications.
The platform uses consumption-based pricing measured through Databricks Units, with costs varying by product, cloud provider and compute configuration. It is aimed primarily at data teams and enterprises that need a unified environment for data and AI workloads.
The platform uses consumption-based pricing measured through Databricks Units, with costs varying by product, cloud provider and compute configuration. It is aimed primarily at data teams and enterprises that need a unified environment for data and AI workloads.
Understanding Databricks
How to use it?
- Step 1: Build enterprise data pipelines
- Step 2: Run large-scale SQL analytics
- Step 3: Train and deploy machine learning models
- Step 4: Develop retrieval and generative AI systems
- Step 5: Govern data and AI assets
Detailed analysis
Databricks combines data engineering, analytics, machine learning and AI development on a lakehouse architecture. Organizations use it to process large datasets, build data pipelines, run SQL analytics, train and deploy machine learning models and develop generative AI applications.
The platform uses consumption-based pricing measured through Databricks Units, with costs varying by product, cloud provider and compute configuration. It is aimed primarily at data teams and enterprises that need a unified environment for data and AI workloads.
Features, use cases & integrations
Features & use cases
- Lakehouse data architecture
- Data engineering and pipelines
- Databricks SQL analytics
- Machine learning and MLOps
- Model serving and generative AI
- Governance with Unity Catalog
- Build enterprise data pipelines
- Run large-scale SQL analytics
- Train and deploy machine learning models
- Develop retrieval and generative AI systems
- Govern data and AI assets
Integrations
- AWS
- Microsoft Azure
- Google Cloud
- Power BI
- Tableau
- dbt
Pricing, advantages & limitations
Pricing
- Databricks Free Edition is a no-cost option for learning and experimentation, with one serverless workspace and daily fair-usage limits. Databricks also offers a 14-day free trial for business evaluation with up to $400 in usage credits. Paid production accounts use consumption-based pricing; actual costs depend on the product, compute, cloud and usage.
👍 Advantages
- Broad unified data and AI platform
- Scales to complex enterprise workloads
- Strong collaboration for data teams
- Large integration ecosystem
👎 Limitations
- Pricing can be complex
- Requires cloud and data engineering expertise
- Costs depend on compute configuration and usage
FAQ & alternatives
FAQ
What is a Databricks DBU?▶
A Databricks Unit is a normalized unit used to price processing capacity across Databricks products.
Does Databricks have a free edition?▶
Databricks offers a Free Edition for learning and experimentation, and may also offer trials for paid environments.
Alternatives
- Snowflake
- Google BigQuery
- Microsoft Fabric
- Amazon SageMaker
- Dataiku
User reviews
Reviews of Databricks
No reviews have been published yet.
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