#118- The AI meets DB wave is here
What I predicted is already playing out
When I first wrote about the AI x DB shift earlier in Jan this year, it was mostly a forward-looking thesis. I was seeing cracks in the old database model which still had storage-based pricing, limited compute, legacy ops. I was reading, thinking, and spotting early signs of something new- databases built not just to store data, but to activate it.
Fast forward 2 quarters and a wave of M&A activity has confirmed what I suspected. The market is quietly rewriting the definition of a database and the buyers are telling us what the future looks like.
The core shift is from passive storage to active compute
Let’s recap the shift in plain terms:
Old world: Databases were priced by GB stored and rows queried. They sat quietly behind BI apps and dashboards
AI world: The database is the application. It stores vector embeddings, serves sub-millisecond queries, supports streaming pipelines, and feeds LLMs directly
Storage is free. Speed, scale, and compute are the new billing surfaces. And whoever owns this AI-native data layer owns the developer.
Now look whats happening
A quick rollup of recent moves-
Snowflake acquired Crunchy Data (2nd June 2025): A play for PostgreSQL strength + open source credibility. Snowflake has to go beyond tabularSQL and this brings vector and hybrid cloud possibilities
Databricks acquired Neon for $1B (14th May 2025): Neon’s architecture (compute-storage separation, Postgres-compatible, cloud-native) fits perfectly into Databricks’ AI native ambitions. Warehousing is passe. Its about real time inference and streaming pipelines
IBM acquired DataStax (25th Feb 2025): Cassandra is built for massive scale and real time ops. IBM wants to feed this into WatsonX to own the inference ready data layer
What this confirms
Every one of these deals aligns with my AI x DB thesis:
Storage is no longer a differentiator, compute is
Databases are no longer utilities, they’re infra
Developer mindshare isn’t a nice to have, it’s the wedge
Pricing is no longer per TB, it’s per millisecond and per vector query
AI isn’t a layer on top, it’s built into the core product loop
The model has shifted. The market knows it. And now the consolidation phase has begun
So whats next
If the first wave was about proving out vector DBs and AI ready infra, the next wave will focus on:
Verticalized AI native DBs- Optimized for sectors like healthcare, logistics, manufacturing, or finance
Low-code/zero-config AI integrations- The StripeXAI data equivalent will come from DB players, not MLOps startups
Bundles of storage + compute + models- Monetization will look more like AWS Lambda or Snowflake credit models than classic SaaS
Expect more M&A. Expect price wars on storage. And expect the real value to accrue to platforms that abstract complexity and own the compute layer
And a closing note…
Please lets not take this as a victory lap. This is a timestamp. We’re in the middle of the great database replatforming…and the winners wont just store your data. They’ll run your models, optimize your compute, and charge you for every intelligent operation
If you’re a founder or investor in this space, the window is now