Databricks brings all your data, reporting and AI together on one platform, in your own cloud. Here is what that means, in plain language.
In most organisations, data lives in many places: source systems, spreadsheets, an older data warehouse and a few AI experiments on the side. Every team copies data into its own tool, the numbers don't match and nobody is quite sure who can see what. Databricks replaces that patchwork with one shared foundation.
One copy of your data, one set of rules and the same numbers for everyone.
Databricks is built on a lakehouse: an architecture that combines the best of two older approaches.
Cheap, flexible storage for every type of data. But hard to keep reliable and fast.
Reliable and fast for reporting. But costly, and built for neat tables only.
The low cost and flexibility of a lake, with the reliability and speed of a warehouse. On open formats, so you are never locked in.
The Databricks Data + AI Platform is built in four layers. You don't need all of them on day one: most organisations start with the first layer and add the rest when there is a real use for it.
One copy of your data in open formats, with no lock-in.
Your data stored once, in open formats such as Delta Lake and Apache Iceberg, ready for both reporting and AI.
More on databricks.com ↗Brings data in from your source systems, transforms it and schedules the pipelines that keep it up to date, all in one place.
More on databricks.com ↗An operational, Postgres-based database inside the platform, so apps and AI agents can work with live data next to your analytical data.
More on databricks.com ↗One place to manage who sees what, data quality and costs.
One place to decide who may see what, trace where data comes from, find the right datasets and govern AI assets in the same way.
More on databricks.com ↗Keeps AI use under control: who may use which models, agents and tools, and what it costs.
More on databricks.com ↗Dashboards and AI that know your KPIs and definitions. Everyone works with the same number.
A warehouse experience for analysts and BI tools: fast SQL straight on the data in your lakehouse, without copying it elsewhere.
More on databricks.com ↗Dashboards built directly on your governed data, with AI that helps you build them and explain the numbers.
More on databricks.com ↗Lets business users ask questions about their data in plain language, with answers grounded in your own KPIs and definitions.
More on databricks.com ↗AI assistants, predictions and apps that run on your own data.
Build, evaluate and run AI agents on your own data, with the model of your choice, and take them into production on one governed foundation.
More on databricks.com ↗Build and run secure data and AI apps directly inside Databricks. Security and governance come with the platform, so no separate hosting is needed.
More on databricks.com ↗No, not in one go. Many organisations start with one use case next to their current setup and move over step by step, once the value is clear.
Databricks charges for what you use, in so-called DBUs, on top of your normal cloud costs. There is no large licence up front. What you pay depends heavily on how the platform is set up, which is why we look at cost control from day one.
That depends on where you start. Most organisations begin with one use case and build from there. We are happy to give you a realistic estimate for your situation.
All three are modern data platforms. Databricks stands out for its open formats, its strength in data engineering and AI, and the fact that it runs on all three major clouds. Which one fits best depends on your situation, and we are happy to help you compare honestly.
Not to get started. You can begin with a partner and build up your own team over time. We help with both: building the platform and making your team self-sufficient.
We are happy to explain it in your context, without obligation.