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Starburst is a data lake analytics platform. It’s designed to help users work with structured data at scale, and is built on the open source platform, Trino. Adam Ferrari is the SVP of Engineering at Starburst. He joins the show to talk about Starburst, data engineering, and what it takes to build a data lake.

Building scalable software applications can be complex and typically requires dozens of different tools. The engineering often involves handling many arcane tasks that are distant from actual application logic. In addition, a lack of a cohesive model for building applications can lead to substantial engineering costs. Nathan Marz is the creator of Rama, which is

SurrealDB is the result of a long-time collaboration between brothers Tobie and Jaime Morgan Hitchcock. The project has modest origins and started merely to support other projects the brothers were working on. However, over time the project grew and in 2021  they started working on it full-time. Since then the project has gained serious adoption.

Maritime logistics is the process organizing the movement of goods across the ocean. Historically, this has been a challenging problem because of the multinational nature of shipping, as well as piracy, smuggling, and legacy technology. It’s also profoundly important for security reasons, and because 90% of what we buy travels over the oceans. Ocean vessels

Data breaches at major companies are so now common that they hardly make the news. The Wikipedia page on data breaches lists over 350 between 2004 and 2023. The Equifax breach in 2017 was especially notable because over 160 million records were leaked, and much of the data was acquired by Equifax without individuals’ knowledge

If you’re a sports fan and like to track sports statistics and results, you’ve probably heard of Sofascore. The website started in 2010 and ran on a modest single server. It now has 25 million monthly active users, covers 20 different sports, 11,000 leagues and tournaments, and is available in over 30 languages.   Josip

Cloud-based software development platforms such as GitHub Codespaces continue to grow in popularity. These platforms are attractive to enterprise organizations because they can be managed centrally with security controls. However, many, if not most, developers prefer a local IDE. Daytona is aiming to bridge that gap. It’s a layer between a local IDE and a

Knowledge graphs are an intuitive way to define relationships between objects, events, situations, and concepts. Their ability to encode this information makes them an attractive database paradigm. Hume is a graph-based analysis solution developed by GraphAware. It represents data as a network of interconnected entities and provides analysis capabilities to extract insights from the data.

Observability software helps teams to actively monitor and debug their systems, and these tools are increasingly vital in DevOps. However, it’s not uncommon for the volume of observability data to exceed the amount of actual business data. This creates two challenges – how to analyze the large stream of observability data, and how to keep

The importance of data teams is undeniable. Most companies today use data to drive decision-making on anything from software feature development to product strategy, hiring and marketing. In some companies data is the product, which can make data teams even more vital. But there’s a common problem – analyzing data is hard and time consuming.

Today it’s estimated there are over 1 billion websites on the internet. Much of this content is optimized to be viewed by human eyes, not consumed by machines. However, creating systems to automatically parse and structure the web greatly extends its utility, and paves the way for innovative solutions and applications. The industry of web

There are hundreds of observability companies out there, and many ways to think about observability, such as application performance monitoring, server monitoring, and tracing. In a production application, multiple tools are often needed to get proper visibility on the application. This creates some challenges. Applications can produce lots of different observatory observability data, but how