AcquiredHow AWS Became a Victim of Its Own Success
David Rosenthal on aWS’s rare misstep: data warehousing and product sprawl challenges.
In this episode of Acquired, featuring David Rosenthal and Ben Gilbert, How AWS Became a Victim of Its Own Success explores aWS’s rare misstep: data warehousing and product sprawl challenges The hosts argue that despite AWS’s exceptional track record, it notably missed the modern cloud data warehouse opportunity that Snowflake capitalized on.
AWS’s rare misstep: data warehousing and product sprawl challenges
The hosts argue that despite AWS’s exceptional track record, it notably missed the modern cloud data warehouse opportunity that Snowflake capitalized on.
They frame Snowflake’s rise as evidence that Redshift didn’t fully meet developer expectations out-of-the-box, partly due to AWS’s scale-driven constraints around security, operations, and SLAs.
They also suggest AWS built Redshift to fight the “last battle” (Oracle-style warehouses moved to cloud) rather than serving a newer customer segment with different needs.
Finally, they discuss AWS becoming “alphabet soup” with too many services, prompting a shift toward clearer vertical solutions and guardrails to reduce customer confusion—while AWS still dominates revenue and operating income.
Key Takeaways
Snowflake’s success highlights a rare AWS product miss.
The hosts call data warehousing potentially AWS’s “biggest failure,” noting Snowflake became a ~$50B standalone company while running largely on AWS infrastructure.
AWS’s enterprise-scale obligations can slow product elegance.
As a “trusted partner” to IT departments, AWS must meet extensive security, operational, and SLA commitments, which can hamper shipping an intuitive, opinionated product quickly.
Developer-first defaults can beat customizable infrastructure.
They argue Redshift often requires significant customization, while Snowflake is compelling “out of the box,” echoing the early AWS playbook of delighting individual developers.
Redshift was positioned for legacy migration, not new segments.
Citing Ben Thompson, they suggest AWS aimed Redshift at “Oracle-style” warehouse replacement, while many Snowflake customers wouldn’t have been Oracle customers at all.
AWS’s breadth became confusing as service count exploded.
The “two-pizza team” model produced many services without a cohesive strategy, making the console and branding feel overwhelming and hard to navigate.
AWS is shifting messaging from features to solutions.
They observe keynotes moving away from celebrating dozens of new features toward pitching industry vertical solutions, case studies, and clearer “what to do” guidance.
Market leadership cushions the impact of these weaknesses.
Even with missteps and cleanup efforts, AWS’s revenue and operating income leadership makes the strategy hard to challenge in aggregate.
Notable Quotes
“Data warehouses. How is Snowflake its own fifty billion dollar company?”
— Ben Gilbert
“It’s probably AWS’s biggest failure, and the question is, why?”
— Ben Gilbert
“They’re a victim of their own success on this front.”
— Ben Gilbert
“It’s right there in the name. They’re fighting Oracle. They’re fighting the last battle with Redshift.”
— Ben Gilbert
“AWS has kind of been Alphabet soup.”
— Ben Gilbert
Questions Answered in This Episode
What specific “out-of-the-box” developer experiences did Snowflake nail that Redshift historically made harder or more customizable?
The hosts argue that despite AWS’s exceptional track record, it notably missed the modern cloud data warehouse opportunity that Snowflake capitalized on.
How did AWS’s security/SLA/operational requirements concretely slow or constrain Redshift’s product design compared to a smaller, focused company?
They frame Snowflake’s rise as evidence that Redshift didn’t fully meet developer expectations out-of-the-box, partly due to AWS’s scale-driven constraints around security, operations, and SLAs.
In what ways did Redshift’s positioning as an “Oracle-style warehouse in the cloud” limit its appeal to emerging analytics customers?
They also suggest AWS built Redshift to fight the “last battle” (Oracle-style warehouses moved to cloud) rather than serving a newer customer segment with different needs.
Which AWS internal incentives (two-pizza teams, service launches, metrics) most contributed to the ‘alphabet soup’ problem?
Finally, they discuss AWS becoming “alphabet soup” with too many services, prompting a shift toward clearer vertical solutions and guardrails to reduce customer confusion—while AWS still dominates revenue and operating income.
What would a more cohesive AWS data warehousing strategy have looked like—better Redshift, a separate new product, or an acquisition?
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