Measured on an M1 with the machine's own power sensors, a photo-ingest workload through 8DB used about 34 joules per gigabyte written against about 130 through SQLite. The reasons are structural, not tuning: a write-optimised tree writes fewer bytes, indexes built at write time remove the background re-indexing daemons, and relevance-gated sync moves only what another device needs. Here is the measurement, the mechanisms, and what they project to for an iPhone's and a Watch's day, with every assumption in the open.
6 min readEnergy per gigabyte measured, April 2026, rerun scheduled · Daily figures are estimates with published assumption setsRead article ↗
The promise of intelligence that never leaves the phone is only as good as the data layer under it. A model retrieving from a store that cannot say where a fact came from, who may see it, or how sure to be will give private answers that cannot be trusted. 8DB is the retrieval layer built for that setting: multi-anchor search that returned 3.6 times the precision of full-text search on the questions people actually ask, traversal that enforces clearance on every hop, and a privacy registry that decides at write time what may ever leave the device.
5 min readMulti-anchor retrieval measured on M1, May 2026 · Governed traversal integration-tested · Registry and workloads exercised on synthetic dataRead article ↗
Every app on an Apple device keeps its data in the same embedded engine, behind a C interface that has not changed in decades. Put 8DB underneath it and the device gets a store that is faster than SQLite on its drop-in write path, carries provenance, confidence and governance as storage columns, answers graph, search, spatial and face-match queries from one substrate, and runs at the same speed on an M1 as on a desktop chip with six times the cache. Here are the measurements, with the host and date on every one.
6 min readCriterion runs on one M1 host with 95% intervals · Estimates labelled with their assumption setsRead article ↗
8DB gives an application three ways to write. The drop-in path speaks SQLite's C interface, preserves read-your-own-writes, and inserted about 2.9 times faster than SQLite on the same M1 in the same run. The native path inserted in 99 nanoseconds, about fifteen times faster. The third path costs more per call because it computes confidence, provenance, governance, a perceptual hash and cross-modal indexes on every write, replacing a pipeline of separate passes with one. Here is the benchmark and the trade each path makes.
5 min readsqlite_comparison_bench, Criterion, one M1 host, 20 May 2026 · 95% intervals · SQLite measured in the same runRead article ↗