Here’s a comprehensive, up-to-date table showing which of the features/technologies in your list are supported natively by Databricks with a paid license (as of 2025), and which require integrations or are only partially supported.
Databricks Feature Coverage Table (2025, Paid License)
| Feature / Term | Databricks Paid Support? | Details / Notes |
|---|---|---|
| ETL | ✅ Full Support | PySpark, SQL, Delta Live Tables, Jobs |
| Data Engineering | ✅ Full Support | Core platform focus (pipelines, transformations, orchestration) |
| Data Warehousing | ✅ Full Support | Databricks SQL, Delta Lake, Serverless SQL Warehouses |
| Data Analytics | ✅ Full Support | Notebooks, SQL, dashboards, analytics workflows |
| Data BI | ✅ Full Support | Built-in dashboards, BI tool connectors (Power BI, Tableau, Looker) |
| Data Science | ✅ Full Support | ML Runtime, MLflow, notebooks, AutoML, Feature Store |
| Data Governance | ✅ Full Support | Unity Catalog, audit logs, RBAC, data lineage, access controls |
| Data Lake | ✅ Full Support | Native (Delta Lake, DBFS, cloud storage integration) |
| Data Analytics Platform | ✅ Full Support | Databricks is a unified analytics/data platform |
| Data Pipeline | ✅ Full Support | Jobs, Delta Live Tables, Workflows, DLT Pipelines |
| Data Lakehouse | ✅ Full Support | Native Lakehouse engine (Delta Lake, SQL, ML, BI, governance) |
| Data Mart | ⚠️ Partial* | Can be built as schema/tables in Lakehouse; no dedicated “mart” product |
| Business Intelligence | ✅ Full Support | Databricks SQL dashboards, native BI integrations |
| Machine Learning | ✅ Full Support | MLflow, notebooks, AutoML, Model Serving |
| Business Analytics | ✅ Full Support | BI dashboards, SQL, notebooks, ad-hoc analytics |
| Big Data | ✅ Full Support | Built on Apache Spark, scales to petabytes, distributed compute |
| DataOps | ✅ Full Support | Jobs API, Workflows, CI/CD, CLI, REST API, alerting, monitoring |
| AI (Artificial Intelligence) | ✅ Full Support | ML, LLMs, GenAI (Mosaic AI), serving, experiment tracking |
| Real-time Analytics | ✅ Full Support | Structured Streaming, Delta, DLT, live dashboards |
| Streaming Analytics | ✅ Full Support | Spark Structured Streaming, Auto Loader, DLT |
| Natural Language | ✅ Full Support | NLP with MLflow, Hugging Face, Python/R; LLM platform (Mosaic AI) |
| Large Language Models | ✅ Full Support | Mosaic AI, LLM hosting, fine-tuning, inference |
| Data Mesh | ⚠️ Partial* | Can implement with Unity Catalog, decentralization patterns |
Legend:
- ✅ Full Support: Native in Databricks platform, out of the box, with paid license.
- ⚠️ Partial: Possible to implement with platform building blocks but not a “1-click” feature.
A Few Clarifications:
- Data Mart: Databricks does not have a “Data Mart” product, but you can create logical data marts using schemas, catalogs, and table-level access in the Lakehouse.
- Data Mesh: Not a product, but Databricks Unity Catalog enables domain ownership, decentralized governance, and multi-team architectures (key for mesh design).
Extra Capabilities in Databricks (Paid License):
- Unity Catalog for enterprise data governance
- Mosaic AI for generative AI and large language model (LLM) training/serving
- Delta Live Tables for declarative, automated pipelines
- MLflow for machine learning lifecycle management
- Jobs & Workflows for scheduling, orchestration, DataOps
- Native connectors for BI/analytics tools
Bottom Line:
Databricks with a paid license is a complete platform for:
- ETL, Data Engineering, Data Warehousing, Analytics, BI, Data Science, ML, AI/LLM, Real-time & Streaming, Governance, and more.
- You can build or enable “Data Mart” or “Data Mesh” patterns using its features, even if not explicitly named as such.