From 35acfc3bfceaceb8cec72607862da0da77cfc40f Mon Sep 17 00:00:00 2001 From: Marvin <33938500+marvin-j97@users.noreply.github.com> Date: Sat, 19 Oct 2024 02:36:23 +0200 Subject: [PATCH] Update README.md --- README.md | 14 +++++++++----- 1 file changed, 9 insertions(+), 5 deletions(-) diff --git a/README.md b/README.md index aeff7df..da73293 100644 --- a/README.md +++ b/README.md @@ -14,23 +14,27 @@ Icelandic, Old Norse: Numbers A simple, embeddable time series database. -It uses as its underlying storage engine, -being able to ingest ~700k data points per second. +## About -The LSM-based storage engine causes no degradation in write ingestion speed, even for large datasets, -has low write amplification (good for SSDs) and compresses the on-disk data (again, good for SSDs). +It uses as its underlying storage engine, allowing around ~700k data points per second to be ingested. + +With the storage engine being LSM-based, there's no degradation in write ingestion speed (even for datasets much larger than RAM), low write amplification (good for SSDs) and on-disk data is compressed (again, good for SSDs). The tagging and querying mechanism is modelled after Datadog's metrics service (). Data points are f32s by default, but can be switched to f64 using the `high_precision` feature flag. -1 billion data points (default config, jemalloc, i9 11900k): +## Benchmark: 1 billion data points + +Default config, jemalloc, i9 11900k - ingested in 1374s (~727k inserts per second) - average memory usage: 100 MB , peak: ~170 MB - query latency for 1 million data points (`AVG | env:prod AND service:db AND (host:h-1 OR host:h-2 OR host:h-3)`): 110ms - disk space: 12 GB +## Basic usage + ```rs use talna::{Database, tagset};