Faster spatial queries. Lower compute costs.

Your busiest spatial queries spend more CPU on engine overhead than on geometry. Scidonia replaces that overhead with compiled code built for your statement, and proves it returns exactly what your database returns.

Evaluate my workload

Where your CPU goes

Tracking, telemetry and geofencing run the same prepared statement millions of times a day. Every run pays for generic row decoding, function dispatch and memory layout. On a point-in-box check, that overhead can cost more than the coordinate maths.

How Scidonia helps

Faster queries

We compile your hottest statement for its plan and your schema, and strip out the per-row engine overhead. Up to 1.95× on simple range-scan benchmarks.

Lower compute costs

Less CPU per query means more throughput from the same hardware, and a smaller bill for high-volume telemetry.

Identical results, proved

A computer-checked proof shows the same rows, values and errors as your engine. No coordinate drift. No dropped rows. No shifted boundaries.

Runs only as proved

A content digest binds the proof to the deployed binary. If the code differs, it does not run.

Is your workload a fit?

A strong fit

Prepared spatial queries run millions of times
Scans, range filters and bounding-box checks
Query plans fixed before execution
Systems where results must be exact: aviation, routing, maritime and utilities

Not a fit

One-off or ad-hoc analytical queries
Queries dominated by disk reads
Plans that change between runs
Queries already fully optimised by standard rewrites