The Real Cost of Oracle Technical Debt: What Developers Learn During Migration
Oracle databases have been around for 40 years. That's a lot of time to accumulate technical debt.
Spencer Kimball, CEO of Cockroach Labs, spends his days helping Fortune 100 companies migrate off Oracle. The technical challenges he sees are consistent: undocumented stored procedures, excessive use of legacy patterns, and architectural decisions made when networking was slow and security wasn't a priority.
"The people that wrote them are gone from our company," Kimball says of the legacy applications his customers want to migrate. "We want help solving this."
PostgreSQL is Eating the World
The first thing to understand about modern database migrations is that developers don't want Oracle's dialect anymore. They want PostgreSQL.
"Postgres is actively eating the world," Kimball says. When Cockroach Labs started 11 years ago, PostgreSQL wasn't the default choice. Now it is.
This shift shows up everywhere. AWS Aurora moved its center of gravity from MySQL to PostgreSQL. Even TiDB, which started as a MySQL engine, recently added PostgreSQL support. IBM's customers are asking for "a Postgres database for the enterprise."
The reason is straightforward: PostgreSQL is the standard for new development. If you're building something new, you're building it on Postgres.
Distributed vs Monolithic: Where Developers Get Surprised
The migration from Oracle to a distributed database like CockroachDB involves more than syntax changes. It requires a shift in thinking.
"Databases have grown up over the last 50 years with this perspective that the database is a tightly coupled monolithic system," Kimball explains. Oracle was built for InfiniBand networks and specialized hardware. Those requirements don't match cloud reality.
The most common surprise? Auto-incrementing IDs.
In a monolithic database, generating sequential IDs is fast because everything runs on one machine. In a distributed system with consensus requirements, that pattern creates bottlenecks.
The solution is UUID generation with node IDs embedded. These IDs are unique across the cluster, sort correctly, and create zero hot spots. It's a small change, but every developer on a migration team needs to understand it.
"Some of this is solved just by retraining developers," Kimball says. "Some of it is done by tooling that will look through a schema and say, 'Here's an auto-incrementing ID. We recommend you replace it with UUID generation.'"
AI is Unraveling Oracle Lock-In
Stored procedures represent Oracle's most effective lock-in mechanism. They were a reasonable architectural choice when network latency was high and database security was limited. DBAs pushed application logic into the database where it could be controlled and protected.
The result is mountains of undocumented code. Sometimes it's PL/SQL. Sometimes it's C routines with no unit tests and no documentation.
AI tools are changing the migration economics. Kimball says AI can analyze legacy stored procedures, generate documentation, create unit tests, and suggest complete migrations to PL/pgSQL (PostgreSQL's procedural language).
"The sharpest decrease in costs is going to come from AI," he says. Where migrations used to require 100+ consultants over three years at a cost of $10 million, AI-assisted approaches can reduce that significantly.
The tools from Cognition, Devin, and even Claude can handle much of the heavy lifting that previously required specialized Oracle knowledge.
Architecture Built for AI Scale
The architectural differences between distributed and monolithic databases matter more as AI workloads increase.
"You can't even get there without a distributed architecture," Kimball says about handling AI-scale traffic. The issue isn't just throughput. It's cost.
Cockroach Labs routinely runs 300-node test clusters for weeks at a time. These clusters contain petabytes of data. Three weeks used to cost $500,000.
Now they run these tests on spot instances and save 80%. "Could you run a traditional database across spot instances?" Kimball asks. "You'd be down most of the time."
A distributed database built for resilience can handle spot instances getting preempted. It replicates, rebalances, and keeps running through the chaos.
The company is targeting a 10x cost improvement through a combination of optimizations: spot instances, multi-tenancy (packing multiple workloads on the same physical database), layered storage (S3, locally attached SSDs, EBS), and continuous performance optimization.
They've already achieved 2x performance improvement on the same hardware this year.
Resilience Under Pressure
Performance benchmarks under ideal conditions don't tell you much about production reality. Cockroach Labs released a "Performance under Adversity" benchmark that measures how databases behave during chaos: pod failures, network partitions, disk stalls.
They tested CockroachDB against Oracle GDD 23ai (the first version of Oracle that can support GDD in a Raft configuration). The results are documented in detail, and the benchmark methodology is open so anyone can reproduce it.
CockroachDB encountered 56 errors resulting in 51 seconds of downtime across all chaos tests. Oracle GDD encountered 300 errors resulting in 369 seconds of downtime (over six minutes).
That's 5x more resilient.
The difference matters most during "grey failures"—those problems that don't immediately take the database offline but slowly degrade latency and breach SLAs.
The Migration Path Forward
If you're stuck on Oracle and planning a migration, here's what to focus on:
Audit your stored procedures. Use AI tools to document what you have before you start planning the migration. You probably have more technical debt than you think.
Understand distributed architecture patterns. Auto-incrementing IDs are just one example. Get your team trained on how distributed consensus works and where the architectural differences matter.
Test for resilience, not just performance. Peak performance under ideal conditions matters less than consistent performance under realistic failure scenarios.
Factor in the full cost. Don't just compare license fees. Include the cost of downtime, the complexity of running the database, and the total cost of ownership over time.
The cloud forced many companies to reconsider Oracle. AI is accelerating that shift. If you're going to modernize anyway—and you probably are—make sure you understand the technical implications before you start.