Taking charge of Tables with OpenHouse

In the world of Big Data Management, there's always a tussle between control and flexibility! Cloud data warehouse solutions maintain tight control over the systems, which allows data infrastructure teams to ensure proper governance, data integrity, security, and performance. However, these systems often suffer from a lack of flexibility and scale. That's where open source data lake(house) systems come into play.

At LinkedIn, we self-manage an open source data lakehouse deployment, and we have faced challenges in providing a managed experience for our end-users. Loss of managed experience often means our end-users have to deal with low-level infra concerns, diluting their core product focus. Moreover, our data infra teams are left with little control on the system we operate, making it harder for us to regulate proper governance and optimization.

Control that liberates is a paradoxical idea, where a well implemented control mechanism can actually empower data infra teams to “regain control” so that they can govern better, and liberate end-users from low level infra concerns by providing them a fully managed offering.

OpenHouse is materialization of this idea!