Support for a diverse set of use cases including streaming, analytics, data science, and machine learning.Interoperability with any system or cloud that adheres to open standards.Modularity so that service use is use-case driven.Better cloud economics with autoscaling that adjusts cloud resources infrastructure to match the actual demand.Infrastructure (OCI) native services that are managed by Oracle and that reduce operational overhead The ability to leverage multiple compute engines, including open source engines, to process the same data for different use cases to achieve maximum data repurposing, liquidity, and usage.The ability to fully decouple storage and compute resources and to consume only the resources needed at any point in time.Governance and fine-grained data security that leverages a zero-trust security model.Diverse data type support in an enhanced multimodel and polyglot architecture.Seamless data and information usage without the need to replicate it across the data lake and data warehouse. ![]() ![]() Use this architecture to leverage the data for business analysis, machine learning, data services, and data products.Ī data lakehouse architecture combines the capabilities of both the data lake and the data warehouse to increase operational efficiency and to deliver enhanced capabilities that allow: This architecture combines the abilities of a data lake and a data warehouse to provide a modern data lakehouse platform that processes streaming data and other types of data from a broad range of enterprise data resources.
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