serilog-sinks-seq VS db-benchmarks

I dont know why you want to use Graylog, but just fyi maybe https://datalust.co/seq is a alternative.

You could use something like Seq to stream all the logs back to you.

Valuable related discussion: https://www.reddit.com/r/devops/comments/13ab0l5/lightweight...

Highlights:

* Grafana and Loki seems to be favorite

* https://datalust.co/seq is the easiest to deploy (single container)

* https://github.com/tstack/lnav CLI based tool

https://datalust.co/seq (my employer) uses a custom database built with Rust. We are about to remove the last C# database code because, as the previous commenter noted, garbage collection and databases don't mix.

Over the next few years I expect we will see a lot of new databases written in Rust.

https://blog.datalust.co/what-will-seq-vnext-look-like-on-th...

I know I’m a little late to the game, but check out Seq. If you use Docker, you can deploy Seq and Seq-input-gelf Docker containers, set gelf as the default logging driver in your daemon.json, and point it at you Seq instance. That’s pretty much it. Seq also accepts a bunch of other log inputs, like Greylog, for things that don’t run in Docker.

There are several popular logging servers that store and process structured log data. The ones I currently know are SigNoz, Seq, New Relic and Kibana. The latter is, in a nutshell, a user interface to visualize Elasticsearch data.

Another for Seq.

Seq for centralized logging in both development and production environments https://datalust.co/seq

Seq has a free option for individuals - https://datalust.co/seq

> I decided to experiment with this setup and the NY Taxi Dataset. The initial goal was to populate ElasticSearch with ~14 million rows, loading data from a compressed parquet file of ~350 MB.

> I tried multiple times, but the operation failed continuously, due to JVM memory constraints

Here's a script https://github.com/db-benchmarks/db-benchmarks/blob/main/tes... which loads 1.7B NYC taxi ride documents into Elasticsearch.

In general, you are correct about another missing key: since we added an exception for MySQL by including two keys, we should perhaps optimize it to the maximum and add the rest as well. However, it would be better to make this more visible directly within the results then. I've created a task about it https://github.com/db-benchmarks/db-benchmarks/issues/30 . Thank you for pointing this out. If you see more issues, feel free to file them on github.

> It's interesting to note that Elasticsearch and Opensearch are general purpose search engine, Solr as well. They are all powered by Lucene, the popular and performant search engine library.

Another search engine which can be considered general, is not based on Lucene and is not less powerful than Elasticsearch/Solr is Manticore Search [1]

[1]: https://github.com/manticoresoftware/manticoresearch

> I would love to see some benchmarks by category :)

I'd love too. We started this work on db-benchmarks [2] , hopefully we'll have resources to continue it. Contributions are very welcome. It's 100% opensource [3]

[2]: https://db-benchmarks.com/

Comparing full-text search engines on queries that aren't full-text search are of course slow, these tests should be adapted to the proper usage of the tested DBs and not just benchmarked across the board..

Example: https://db-benchmarks.com/?cache=fast_avg&engines=elasticsea...

Clickhouse: no tuning , just CREATE TABLE ... ENGINE = MergeTree() ORDER BY id and standard clickhouse-server docker image.

MySQL and Percona Server for MySQL: no tuning , just CREATE TABLE ..., FULLTEXT(story_text,story_author,comment_text,comment_author))and standard mysql docker image .

https://db-benchmarks.com is a platform and a framework for making the most fair, transparent and open source database and search engines benchmarks. No more benchmarketing, because: