The narrative here is that the evolution of database systems has always been in response to a rapidly changing landscape of "constraints", e.g. - The challenge

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