what is the databricks lake house platform databricks and the databricks lake house platform in this video you'll learn about databricks and the databricks lake house platform you'll also learn how to define the databricks lighthouse platform give examples of how to solve Big Data challenges and describe how it benefits data practitioners databricks was founded in 2013 By the original creators of Apache spark Delta Lake and ml flow as the world's first and only lake house platform in the cloud databricks combines the best of data warehouses and data Lakes to offer an open and unified platform for
data and AI databricks is the inventor and Pioneer of the data lake house architecture coining the term in the research paper lake house a new generation of open platforms that unify data warehousing and advanced analytics co-authored by the databricks founders UC Berkeley and Stanford University in 2021 the lake house Paradigm is designed as the ideal data and AI platform for all data types that is open with a single security and governance model not only is it designed to manage all data types but it is cloud agnostic so data can be governed wherever it is stored
because its purpose is to support all major data and AI workloads teams can easily collaborate and access all the data they need to keep innovating and improving all of these architectural features are realized on the databricks lake house platform including the reliability and performance of Delta Lake as the data Lake foundation a fine-grained governance for data and AI with unity catalog and support for persona-based use cases for all data team members the databricks lake house platform architecture also provides instant and serverless compute where databricks provides and manages the compute layer on behalf of the customer
combining the best elements of data warehouses such as reliability governance and performance with the openness and flexibility and machine learning support of data Lakes the databricks lighthouse platform is a single platform that unifies data warehousing and AI use cases this unified approach eliminates the challenges caused by previous data environments such as data silos complicated structures and fractured governance and security structures to reiterate the benefits of the data lake house platform first it is simple by providing a unified platform and eliminating the complexity and expense that stands in the way of achieving the full potential of
data analytics and AI initiatives it is open with a foundation on Delta Lake for reliability and performance while avoiding proprietary systems thus making it easy to share data unrestricted it allows you to build the ecosystem you need with open source projects and the vast network of databricks Partners and it is multi-cloud allowing you to work on the cloud platform currently in use with a consistent management security and governance experience The databricks Lakehouse platform supports the workloads for data teams including data warehousing data engineering data streaming and data science and machine learning and speaking of Partners
The databricks Lakehouse platform provides the flexibility to use your existing infrastructure share your data and build a modern data stack with unrestricted access to open source data projects and the broad databricks partner Network including but not limited to those shown here
