The narrative here is that the evolution of database systems has always been in response to a rapidly changing landscape of "constraints", e.g.<p>- The challenge of open R&D collaboration -> Postgres & MySQL<p>- The ineffectiveness of one-size-fits-all DB engines -> 19 database services at AWS<p>- Shared disk architectures being difficult to scale -> cloud object storage<p>- High storage costs limiting the applicability of data analysis -> cloud data warehousing<p>...and so on. Followed by a summary of the biggest constraints that databases face today:<p>> What limits the application of infinite cores?<p>> 1. Data: inability to get data to processor fast enough<p>> 2. Power: cost rising and will dominate<p>Conclusion (spoiler!):<p>> ML central to DB going forward + opportunities with H/W specialization = big database innovations still coming