The Postmodern Data Stack is AI

After a decade of success, the modern data stack has entered consolidation. What comes next?

The postmodern data stack is AI.

The modern data stack created more than $100 billion in market cap with a simple promise : move the data via ETL, transform it inside a cloud data warehouse, put a semantic layer on top of it to unify metric definitions, & analyze it through BI.

This worked brilliantly for structured data, numerical data found within tables. But AI & businesses thrive on unstructured data, such as call transcripts, status reports, web searches, & PDFs.

The semantic layer, especially within large organizations with huge data sets, must now combine structured & unstructured information at scale, critical because all of it feeds AI & powers agents.

Strategic acquisitions prove this shift is already underway. The Datadog acquisition of Metaplane¹, the Snowflake acquisition of Observe², & the ClickHouse acquisition of Langfuse³ are the most concrete strategic moves reinforcing this fusion.

All of these initial acquisitions focus on observability & understanding AI systems. First, the volumes of data are enormous & essential to sustaining the breakneck pace of AI innovation.

Second, observability helps inform roadmaps : how are customers using AI? Where are they not successful? How can a business help them grow & expand?

We will see many more acquisitions that lead to a combined postmodern & AI stack, accelerating the consolidation that has already started. In addition, there are many pieces of the AI stack not represented here, such as evaluations & agent orchestration.

Those are next.