A data lakehouse combines the best elements of data lakes and data warehouses in one architecture, helping organizations reduce costs and deliver on data and AI initiatives faster. The Databricks Data + AI Platform is built on lakehouse architecture, which unifies data, analytics and AI rather than keeping them in separate systems. Built on open source and open standards, it simplifies your data estate by eliminating the silos that historically complicate data and AI. This single architecture covers integration, storage, processing, governance, sharing, analytics and AI for both structured and unstructured data.

Rather than requiring separate systems for structured analytics and raw or unstructured data storage, lakehouse architecture combines the best elements of data lakes and data warehouses into one platform. With Databricks, this means one architecture for integration, storage, processing, governance, sharing, analytics and AI, one approach for structured and unstructured data, one end-to-end view of data lineage and provenance, and one toolset for Python and SQL, notebooks and IDEs, batch and streaming across all major cloud providers. This unification is designed to eliminate the silos that historically complicate maintaining separate data lake and data warehouse systems.

Whether you're a startup or a global enterprise, Databricks lakehouse architecture is built to meet the demands of your business at any scale. It's designed for data and AI teams working across integration, storage, processing, governance, sharing, analytics and AI, using both structured and unstructured data. Because it supports Python and SQL, notebooks and IDEs, batch and streaming, and all major cloud providers, it can serve data engineers, data scientists, analysts and AI teams within the same organization.

Lakehouse architecture is underpinned by the widely adopted open source projects Apache Spark™, Delta Lake and MLflow. It is globally supported by the Databricks Partner Network, and Databricks keeps your data under your control, free from proprietary formats and closed ecosystems. Delta Sharing further provides an open way to securely share live data from your lakehouse to any computing platform without replication or complicated ETL.

It does emphasize that automatic optimization for performance and storage is designed to deliver the lowest total cost of ownership of any data platform. To get exact pricing for your use case, you can try Databricks for free and evaluate the platform directly.

You can try Databricks for free directly from the Data Lakehouse product page. This lets you explore lakehouse architecture running on the Databricks Data + AI Platform, including its unified approach to data engineering, data warehousing, governance, data science and AI. The same free trial applies whether you're evaluating the platform as a startup or as part of a larger enterprise team.

The Databricks Lakehouse supports a broad set of workloads, including data sharing, data engineering, data governance, data warehousing, artificial intelligence, data science, real-time streaming and the Databricks Marketplace. It also delivers world-record-setting performance for both data warehousing and AI use cases, including generative techniques like large language models (LLMs). This lets teams run these workloads on one platform instead of stitching together separate tools.