Where the guarantees
actually come from.

Events enter fixed-capacity circular ring buffers with atomic sequence counters, so nothing allocates on the hot path. A background governor batches them with AVX-512 / ARM NEON vectorization and compresses the result into Apache Arrow columnar chunks. Because the buffers are fixed at compile time and the counters are atomic, a producer never blocks a consumer; that is the property that keeps a burst of incoming events from turning into a latency spike.

No repeated SQL table scan over history. SciBor computes mathematical derivatives over weighted Z-sets instead, so aggregates such as rolling means, variance spikes and scores update in sub-microseconds ($O(\Delta)$ time). The host app can then query its own telemetry live. That matters most on the client, where a full scan across months of telemetry would otherwise land on the same thread that is trying to paint a frame.

Four index engines sit in one embedded store. Vector search (HNSW) covers similarity and personalization. Graph storage holds component topologies and user journeys. BM25 handles full text. Arrow columnar takes the aggregates. Keeping all four in one process is the point — a similarity lookup, a topology walk and a rolling aggregate can be answered without a network hop between three separate systems.