Relational warehouses were built for yesterday’s batch loads and predictable volumes. Today you’re juggling click‑streams, IoT feeds, and AI‑ready datasets that arrive in seconds and scale to petabytes. The result? Expensive scale‑ups, sluggish queries, and analysts stuck waiting for the warehouse to catch‑up.
By decoupling low‑cost, limitless object storage from elastic compute, Databricks lets you land every byte, spin up power only when you need it, and pay strictly for the minutes you run. Stream, batch, or machine‑learning workloads—one unified platform handles it all, so your team can focus on extracting insights, not wrestling infrastructure.
The best of both worlds in one platform.
Unify analytics, AI, and streaming on a single, open platform. The Lakehouse sits on Delta Lake—an ACID‑compliant storage layer that turns cloud object storage into a high‑performance engine for structured, semi‑structured, and unstructured data. One security and governance model spans every workload and cloud, eliminating silos while cutting cost and complexity.
With Microsoft Entra ID. Extend the Azure AD investment you already trust & grant instant, secure Databricks access with full SSO, MFA, and conditional‑access policies, all managed in one place.
Force all Databricks traffic—compute and storage—through private endpoints, then lock it down with Azure Firewall application and network rules. No public egress, no data leaks.
Databricks UIs are public by default. Shield them with Private Link and Azure Firewall so only corporate IPs or VPN ranges get through—seamless sign‑in, zero public exposure.
One governance layer for the entire Lakehouse. Cloud admins set the top‑level guardrails once; Databricks admins then grant table‑level access to teams and users through a friendly UI or simple SQL. No deep IAM rewiring, no network gymnastics—just secure, compliant analytics with a clear split of responsibilities and minimal retraining.
With the same pipeline. Databricks Auto Loader’s cloudFiles API watches your object storage for new files, then ingests them in real‑time or on a defined schedule with exactly the same code.
Flip a single flag to move from micro‑batch to continuous streaming; schema inference, file deduplication and automatic checkpointing handle the rest. One declarative pipeline, limitless data velocity.
The lake built into Azure Storage. Handle petabytes—and pump data at hundreds of Gb/s—on the same secure, cost‑efficient backbone you already trust.
ADLS Gen2 turns Azure Storage into a high‑performance landing zone for enterprise‑scale analytics.
We can build and deliver your Databricks platform on Azure whether you need multiple environments (DEV, TEST, PROD) or a fully secured implementation. We can help.
Do you need help or extra resources for ingesting, cleaning and preparing data? Or a data modelling project to prepare your data for Power BI Analytics. We can help.
How do you deploy your Databricks Notebooks and Synapse Data pipelines in a multi-environment platform? It’s all possible using Azure DevOps and Build & Deployment pipelines.
Do you have a greenfield project that you think Databricks can help solve? We can onboard you all way through from Platform Delivery, Data Ingestion, Data Modelling & Power BI Dashboards.
Setting up Databricks as a fully secure service with Private Networking, Key Vault Integration, Secure Data Lake Storage and On-Premise to Cloud access is a complicated process. Let us simplify it with our Azure Data Platform accelerator.
Are you deploying Azure Data Lake Gen2 for high performance? Worried about costs and Storage Tiers? We can help you design your Data Lake and storage options to maximise performance and minimise costs
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