# Data lakehouse · Glossary
A data platform architecture that combines the low-cost, flexible storage of a data lake with warehouse-style features such as transactions, schema enforcement and fast analytical queries.
[Glossary](/glossary) · Data platforms and engineering

# Data lakehouse

     A data platform architecture that combines the low-cost, flexible storage of a data lake with warehouse-style features such as transactions, schema enforcement and fast analytical queries. It aims to serve reporting, data science and AI from one platform.

## Why it matters

     Running a separate lake and warehouse means copying data between them, duplicating governance and reconciling differences. A lakehouse can reduce that duplication and keep raw, refined and modelled data in one governed environment.

     It is an architecture pattern rather than a guarantee. The benefits depend on disciplined data modelling, access control and cost management.

## In practice

     For example, a UK e-commerce group might consolidate clickstream data, order data and product images into a lakehouse, with refined tables for finance reporting and raw data available to its data science team under the same permissions model.

## Where Rodan fits

     Rodan designs and builds lakehouse platforms through [Data and Analytics Engineering](https://rodan.io/data-analytics-engineering) and [Platform and Cloud Engineering](https://rodan.io/platform-cloud-engineering).

## Related terms

- [Data lake](/glossary/data-lake)

- [Data warehouse](/glossary/data-warehouse)

- [Medallion architecture](/glossary/medallion-architecture)

- [Data architecture](/glossary/data-architecture)
HTML: https://rodan.io/glossary/data-lakehouse