Data Lakehouses & Apache Iceberg

Aaron interviews Ivan Lee, founder and CEO of Datasaur, about what it takes to build private, secure AI for regulated enterprises. Lee traces the shift away from third-party model reliance to compliance pressure, IP protection, and cost, and frames the core decision as buy versus ...  Show more

Aaron and Brandon cover what the week's news means for enterprise buyers. They question whether Oracle's reported $664 billion backlog is durable demand or overlapping commitments, and Brandon argues contracted future spend is how enterprise business works. On the labs' "slow dow ...  Show more

<h2>Summary</h2>

Data lakehouse architectures are gaining popularity due to the flexibility and cost effectiveness that they offer. The link that bridges the gap between data lake and warehouse capabilities is the catalog. The primary purpose of the catalog is to inform the ...

<h2>Summary</h2>

A data lakehouse is intended to combine the benefits of data lakes (cost effective, scalable storage and compute) and data warehouses (user friendly SQL interface). Multiple open source projects and vendors have been working together to make this vision a r ...

In this episode, I had the pleasure of speaking with Ken Pickering, VP of Engineering at Going, about the intricacies of streaming data into a Trino and Iceberg lakehouse. Ken shared his journey from product engineering to becoming deeply involved in data-centric roles, highlight ...  Show more

<h2>Summary</h2>

Databases and analytics architectures have gone through several generational shifts. A substantial amount of the data that is being managed in these systems is related to customers and their interactions with an organization. In this episode Tasso Argyros, ...