First look at performance comparison between InfluxDB IOx and VictoriaMetrics

Yesterday, InfluxData released a new product called InfluxDB IOx written in Rust. That solution covers a few different cases compared to VictoriaMetrics but still can be used to store metrics. And as you know, we love to do benchmarks with other metrics storages (influx, scylla, timescale).

We’re always curious about new solutions and approaches in the world of time series, and IOx caught our eye. We were impressed with the product design and introduction. And we wanted to compare to our product, so we did the simplest billy benchmark (see more details here) on a single instance with the following specs: Intel(R) Core(TM) i5–8265U CPU @ 1.60GHz 4 CPU, 32GB RAM, 1TB SSD

It is effortless to use, and we encourage the reader to make the test as well.

The results are following:

Ingest performance — rows/sec (higher is better)

Starting from 1,005,343 rows/sec IOx ingesting performance dropped to 603,077 rows/sec and then remained stable/constant

VictoriaMetrics at start made 5,079,938 rows/sec and 3,9989,69 after two minutes.

Full log:

And for VictoriaMetrics:

Number of datapoints

Number of ingested datapoints (higher is better)

As you can see, VictoriaMetrics, in the first 20 seconds, processed a larger number of datapoints compared to IOx in the whole 130 seconds of the benchmark.

Average speed:

Influx IOx — 684 330 rows/sec
VictoriaMetrics — 4 022 090 rows/sec

As you can see, VictoriaMetrics provides almost six times better ingestion performance — and that impressive result is for a single node. We expect even better performance in cluster comparison but can’t do a proper test, while cluster in influx is a paid feature.

Meanwhile, the cluster version of VictoriaMetrics is free and open-sourced. Please take a look at our site to find out more about VictoriaMetrics solution.

Upd. We got commentary from InfluxData that Influx IOx is in an early stage and not ready for benchmarks. We understand that this project is in the early stages, but we can’t help but try it ourselves. We hope to make a better comparison/evaluation once the product is ready.

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