<p>LinkedIn has open sourced OpenHouse, their control plane for managing tables in data lakehouse deployments. OpenHouse provides self-service management of tables and addresses challenges faced by LinkedIn’s internal data teams. The tool offers features like declarative catalog operations, retention management, data sharing, governance, replication, and Iceberg maintenance. It has streamlined LinkedIn’s dbt implementation, reduced end-user toil, and improved time-to-market for data build tools. OpenHouse integrates with Apache Spark and supports Apache Iceberg for compliance and performance. It is compatible with open source data lakehouses and can be used in a Kubernetes cluster. OpenHouse is customizable and designed to fit diverse environments, offering a managed experience for open source lakehouses. With its open sourcing, OpenHouse aims to reduce operational toil, enhance the developer experience, and improve governance for managing tables in data lakehouse deployments.</p>


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LinkedIn has open sourced OpenHouse, a control plane for managing tables in data lakehouse deployments. OpenHouse offers features like declarative catalog operations, retention management, data sharing, governance, replication, and Iceberg maintenance. It integrates with Apache Spark and supports Apache Iceberg for compliance and performance.

OpenHouse: A Control Plane for Managing Tables in a Data Lakehouse