Accelerate data and AI
with Azure Databricks.
Unify data engineering, analytics, streaming and AI on one open lakehouse, secured the Azure way. We have built and run Databricks platforms from a single workspace to enterprise estates.
The right engine for serious data engineering
Databricks earns its place when the data is big, varied or fast, the engineering is real, and AI is on the roadmap rather than a slide.
Large or multi-domain estates
Many sources, many teams and many domains, each needing its own space under one set of rules.
Heavy engineering and streaming
High-volume batch and streaming pipelines, with Spark doing the work and declarative pipelines keeping it maintainable.
Machine learning and AI
Feature engineering, model training, serving and governed AI on the same data the reports use.
Open formats, no lock-in
Delta tables in your own storage account, readable by Fabric, Power BI and any other engine that speaks Delta.
Smaller estate, or Power BI is the main destination? Microsoft Fabric may fit better.
Compare Databricks and FabricFrom empty subscription to governed lakehouse
Every Databricks platform we build follows the same path, and each step has an Xcelerator behind it, so you start from proven code rather than a blank workspace.
Foundation
DatabricksXcelerator
- VNet-injected workspaces
- Private Link and Azure Firewall
- Entra ID single sign-on
Ingest
DataXcelerator and Lakeflow
- Metadata-driven loads into Bronze
- Auto Loader for files and streams
- Incremental by default
Model
Medallion lakehouse
- Declarative pipelines to Silver and Gold
- Kimball or Data Vault, as fits
- Data quality expectations
Serve
Wherever insight is used
- Power BI and AI/BI dashboards
- Genie Agents and Databricks SQL
- Models and AI services
Governed by Unity Catalog throughout
- Access, row filters and column masks
- Lineage from source to report
- Audit in system tables
- Asset Bundles through DEV, TEST and PROD
Everything from pipelines to AI
Lakehouse engineering
Medallion lakehouses on Delta Lake, with Lakeflow declarative pipelines, Auto Loader and incremental processing.
Governance with Unity Catalog
Catalogs, privileges, row filters, column masks and lineage designed once and applied everywhere.
Databricks SQL and AI/BI
SQL warehouses for analysts, AI/BI dashboards and Genie Agents, and Power BI on the Gold layer.
Machine learning and AI
MLflow experiments, model serving and governed AI services, built on the same tables as your reporting.
DevOps
Databricks Asset Bundles and CI/CD in Azure DevOps or GitHub Actions, so every change is reviewed and repeatable.
Cost and performance
Serverless where it pays, cluster policies where it does not, and table maintenance that keeps queries fast.
