Two years ago, our team faced a critical decision that would define our platform's future. We needed a distributed database that could handle massive scale, maintain strong consistency, and support our growing fintech application. After months of evaluation, we chose FoundationDB over CockroachDB. Today, I'm writing this from the other side of a painful migration back to CockroachDB, having learned expensive lessons about the gap between impressive technology and practical implementation.
The Allure of FoundationDB
FoundationDB seemed like the holy grail of distributed databases. Apple's backing gave it credibility, and its architectural approach was genuinely revolutionary. The promise was intoxicating: unlimited scalability with ACID transactions, a clean separation between storage and compute layers, and performance benchmarks that made other solutions look sluggish.
Our technical evaluation was thorough — or so we thought. FoundationDB's simulation testing framework impressed us deeply. The idea that they could simulate millions of hours of operation and catch edge cases that would take years to surface in production felt like the future of database engineering. The technical papers were pristine, the architecture elegant, and the performance in our synthetic benchmarks was outstanding.
But we made a critical error: we fell in love with the technology instead of solving our problem.
The Red Flags We Ignored
Looking back, the warning signs were there, but we rationalized them away. The documentation, while technically accurate, read like academic papers rather than practical guides. Simple operations required diving into low-level APIs. The community was small and mostly consisted of Apple engineers and a handful of enthusiasts.
Most tellingly, we struggled to find production war stories. Not success stories — those existed — but the messy, honest accounts of what goes wrong at 3 AM when your database decides to misbehave. CockroachDB had plenty of these stories, complete with detailed post-mortems and lessons learned. FoundationDB had marketing materials and conference talks.
We dismissed this as growing pains for a newer open-source project. We were wrong.
The Reality of Production
Six months into production, our relationship with FoundationDB began to sour. The first major issue was operational complexity. While CockroachDB could be managed by our existing DevOps team, FoundationDB required specialized knowledge that took months to develop. Every configuration change felt like defusing a bomb.
The breaking point came during our first major traffic spike. Despite following all best practices, we encountered a cascading failure that brought down our entire platform for six hours. The root cause was a subtle interaction between our application code and FoundationDB's transaction processing that our testing hadn't revealed. The fix required deep knowledge of FoundationDB's internals that took weeks to acquire.
More frustrating was getting help. CockroachDB's community had hundreds of engineers who had faced similar issues. FoundationDB's community consisted of a few dozen people, most of whom worked at Apple and couldn't discuss their specific implementations.
The Hidden Costs
The technical debt accumulated quickly. Every new developer on our team needed weeks of FoundationDB-specific training. Our monitoring and alerting systems required custom solutions. Third-party tools that worked seamlessly with PostgreSQL or CockroachDB needed extensive modification or replacement.
But the real cost was opportunity cost. Our engineering team spent months becoming FoundationDB experts instead of building features that mattered to our customers. We optimized for theoretical elegance instead of practical velocity.
The final straw was our audit. Our compliance team needed detailed explanations of our data consistency guarantees. CockroachDB's documentation made this straightforward. FoundationDB's academic approach to documentation made it nearly impossible to provide the business-friendly explanations our auditors required.
The Migration Back
Migrating from FoundationDB to CockroachDB was complex but not catastrophic. CockroachDB's PostgreSQL compatibility meant most of our application code worked with minimal changes. The operational simplicity was immediately apparent — our first CockroachDB cluster was up and running in hours, not days.
Performance took a small hit initially, but CockroachDB's query optimizer and our improved understanding of distributed database patterns soon had us running faster than our original FoundationDB implementation. More importantly, our team could focus on application logic instead of database internals.
What We Learned
The most valuable lesson was about choosing technology for the right reasons. FoundationDB is genuinely impressive technology, but impressive technology doesn't automatically translate to the right choice for your specific context.
We should have weighted operational considerations more heavily. The database that lets your team move fastest is often more valuable than the database with the best benchmarks. Community size, documentation quality, and ease of hiring matter more than we initially realized.
We also learned to distinguish between technical evaluation and production readiness. Our rigorous performance testing missed the human factors that ultimately determined our success: how quickly could we debug issues, how easily could we scale our team's knowledge, and how much cognitive overhead did the technology introduce.
The Broader Lesson
This experience taught us to be more skeptical of revolutionary technologies, especially when proven alternatives exist. Sometimes the boring choice is boring for good reasons — it's been tested by thousands of teams in production, its rough edges have been smoothed, and its community has developed solutions to common problems.
FoundationDB will likely become an excellent choice as its ecosystem matures, but we learned that being early adopters of infrastructure technology carries hidden costs that are easy to underestimate. For most teams, the cutting edge is a dangerous place to build critical systems.
Have you faced similar decisions between innovative and proven technologies? I'd love to hear about your experiences in the comments. If you found this useful, consider following me for more honest accounts of engineering decisions that didn't go as planned.