Scaling Relationship Discovery Beyond Brute Force

When people hear “relationship discovery,” they assume it’s an algorithm problem.

It isn’t.

It’s a systems architecture problem.

If you have 60,000+ fields, naïve pairwise comparison explodes combinatorially. At scale, brute-force comparison becomes computationally absurd — a bottleneck that could theoretically take centuries

So the real challenge is:

How do you discover structure without collapsing compute?

At Arisyn, we avoid brute force entirely.

We apply:

· Feature-based indexing instead of raw pairwise scanning

· Intelligent filtering based on distinct_num thresholds

· Full extraction for low-cardinality fields

· Sampling-based inclusion comparison for high-cardinality fields

We default to a 100k distinct-value boundary to balance Redis memory and execution time

The system estimates:

· Required memory

· Maximum parallel threads (bounded per database connection limits)

· Execution time

· Cost exposure

Then tasks are distributed with:

· Parallel processing

· Checkpoint recovery

· Pause/resume

· Fault tolerance

Scalability is not about throwing more compute at the problem.

It’s about reducing the search space intelligently.

At enterprise scale, architecture beats brute force.

Every time.