Aliaksandr Valialkin 2024-11-15 14:29:01 +01:00
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@ -119,6 +119,7 @@ See also [case studies](https://docs.victoriametrics.com/casestudies/).
* [Improving histogram usability for Prometheus and Grafana](https://valyala.medium.com/improving-histogram-usability-for-prometheus-and-grafana-bc7e5df0e350)
* [Why irate from Prometheus doesn't capture spikes](https://valyala.medium.com/why-irate-from-prometheus-doesnt-capture-spikes-45f9896d7832)
* [VictoriaMetrics: PromQL compliance](https://medium.com/@romanhavronenko/victoriametrics-promql-compliance-d4318203f51e)
* [How do open source solutions for logs work: Elasticsearch, Loki and VictoriaLogs](https://itnext.io/how-do-open-source-solutions-for-logs-work-elasticsearch-loki-and-victorialogs-9f7097ecbc2f)
### Tutorials, guides and how-to articles

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@ -34,7 +34,7 @@ VictoriaLogs is optimized specifically for logs. So it provides the following fe
- Easy to setup and operate. There is no need in tuning configuration for optimal performance or in creating any indexes for various log types.
Just run VictoriaLogs on the most suitable hardware, ingest logs into it via [supported data ingestion protocols](https://docs.victoriametrics.com/victorialogs/data-ingestion/)
and get the best available performance out of the box.
- Up to 30x less RAM usage than Elasticsearch for the same workload.
- Up to 30x less RAM usage than Elasticsearch for the same workload. See [this article](https://itnext.io/how-do-open-source-solutions-for-logs-work-elasticsearch-loki-and-victorialogs-9f7097ecbc2f) for details.
- Up to 15x less disk space usage than Elasticsearch for the same amounts of stored logs.
- Ability to work efficiently with hundreds of terabytes of logs on a single node.
- Easy to use query language optimized for typical log analysis tasks - [LogsQL](https://docs.victoriametrics.com/victorialogs/logsql/).

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@ -15,7 +15,7 @@ VictoriaLogs provides the following features:
- VictoriaLogs' capacity and performance scales linearly with the available resources (CPU, RAM, disk IO, disk space).
It runs smoothly on Raspberry PI and on servers with hundreds of CPU cores and terabytes of RAM.
- It can handle up to 30x bigger data volumes than Elasticsearch and Grafana Loki when running on the same hardware.
See [these docs](#benchmarks).
See [these docs](#benchmarks) and [this article](https://itnext.io/how-do-open-source-solutions-for-logs-work-elasticsearch-loki-and-victorialogs-9f7097ecbc2f) for details.
- It provides fast full-text search out of the box for [log fields](https://docs.victoriametrics.com/victorialogs/keyconcepts/#data-model)
with high cardinality (e.g. high number of unique values) such as `trace_id`, `user_id` and `ip`.
- It supports multitenancy - see [these docs](#multitenancy).