What is open data infrastructure? How is it different from the modern data stack?

Tristan Handy discusses the merger between dbt Labs and Fivetran to create an open data infrastructure, distinguishing it from the modern data stack (MDS) which has been transformative yet flawed due to integration challenges and limited scalability. The modern data stack enabled fast, scalable data manipulation by integrating software engineering practices but led to tool fragmentation and complex integration issues. In response, "all-in-one" data platforms emerged, offering integrated solutions but at the cost of user choice and potential vendor lock-in. The proposed open data infrastructure aims to overcome these limitations by emphasizing pluggability, standards-based integration, and flexibility in compute engine choice, allowing data teams to maintain control over their data environments while adapting to new AI capabilities. By leveraging open standards and maintaining vendor neutrality, this infrastructure seeks to provide reliable, high-quality data and metadata management, reducing costs and improving collaboration across data teams without sacrificing flexibility or performance.

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