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Lakebase is a new kind of database that merges the reliability and developer experience of Postgres with the scale, governance and analytics power of a data lakehouse. It lets teams run transactional workloads while seamlessly syncing data to analytics and AI systems, without building custom ETL pipelines. The result is one platform where apps, data and models work together in real time.

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A data warehouse is a data management system that stores current and historical data from multiple sources in a business-friendly manner for easier insights and reporting. Data warehouses are typically used for BI, analytics, reporting, data applications, preparing data for ML and data analysis. 

Data warehouses enable quick and easy analysis of business data uploaded from operational systems such as point-of-sale systems, inventory management systems, or marketing or sales databases. Data may pass through an operational data store and require data cleansing to ensure data quality before it can be used in the data warehouse for reporting.

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Databricks offers the only platform built from the ground up for data and AI together. Unlike legacy tools that bolt AI onto analytics after the fact, the Databricks Data + AI Platform was built to bring together data ingestion, transformation, analytics and machine learning in one place — eliminating the need for teams to stitch together three or four different platforms. This represents a reversal of the past decade’s trend toward specialized tools. The Databricks Data + AI Platform is designed around the thesis that unification is the competitive advantage — one copy of data, one processing engine, one governance model across all clouds and all workloads.

Lakehouse architecture brings together the flexibility of a data lake and the reliability of a data warehouse. Delta Lake enforces data quality rules, supports ACID transactions to prevent corruption and offers time travel — the ability to query data as it existed at any prior point.

With open formats like Delta Lake and Apache Iceberg^™, data is portable: you can query it from Databricks today, Spark tomorrow and Trino next year and never move a byte. Customers in competitive evaluations consistently cite openness as one of their primary deciding factors — and Unity Catalog, as an open governance layer, is cited as a unique capability that competitors haven’t matched.