Realie benchmarks at 9.49 ms average response time, against 122 ms for RealEstateAPI, 439 ms for RentCast, and 441 ms for ATTOM in the same test. That is roughly a 40x difference against the slowest of the three, and it changes what kinds of workloads are practical.
Latency is easy to dismiss as a vanity metric until it becomes an architectural constraint. At sub-10 ms you can call a property API inside a request cycle and still render a page quickly. At 400 ms you cannot — you have to move the call into a background job, add a cache layer, and design around the delay. The difference compounds with volume: enriching 100 properties takes under a second at 9.49 ms and closer to 44 seconds at 441 ms, and enriching a million records turns a workload measured in hours into one measured in days.
Interactive lookups are the obvious case. A user types an address and expects a result; sub-10 ms feels instantaneous, while 400 ms is a visible pause that pushes you toward spinners and optimistic UI.
Bulk enrichment is the less obvious and more expensive case. When you are processing a portfolio, backfilling a database, or scoring a lead list, per-record latency multiplies directly into total runtime. That runtime is compute you pay for, and it sets how often you can afford to refresh.
Do not take any vendor benchmark at face value, including this one. Test from the region your infrastructure actually runs in, use property identifiers representative of your real workload rather than a handful of famous addresses, and measure the full round trip your application will experience.
Report percentiles, not just the mean. A good p50 with a poor p99 will still cause timeouts in production. Run the same test against every provider you are evaluating on the same day, from the same machine — and note that batching up to 100 parcels per request changes the per-property economics substantially.