Timber vs Logstash

The Timber interface stands out in the space:

1. It's beautiful, easy, and modern.
2. It's fast. It uses advanced front-end technologies to maximize performance and usability (react, redux, etc).

Timber offers a really great simple search, with a support for advanced features like: term negation, condition grouping (parenthesis), regex, field searches and conditions, etc.

Timber allows you to SQL query your logs just like you would a traditional database. The JOIN support is very powerful.

The retention Timber offers is exceptionally longer. The default is generally 2 - 4 weeks, Timber offers 6 months.

Because Timber fully embraces structured data, graphing is simple, real time, and fast. They provide a number of aggregates you can graph on.

Timber provides native libraries that automatically attach metadata to your logs. They've designed a schema that defines events and context, which normalizes the data and makes querying, alerting, and graphing simple and reliable.

Timber can be installed in < 1 min and usually with a single command. It asks your for your application details and provides 1 set of simple instructions.

Besides the free plan, Timber doesn't impose limits on the number of users, alerts, etc. It's entirely based on the amount of data allowed for the plan. It's refreshingly straightforward.

The alerts are real-time and the approach is thoughtful. Instead of blasting you with alerts every time it's triggered, they change the state of the alert once, notify you once, and then notify you again when the alert is no longer an issue.

Timber's docs are detailed and thoughtful, both for the service as well as the libraries they offer.

Beyond the space your plan is allowed to use, there is no rate limiting.

Logs show up < 3 seconds of when they are generated

There is an official Docker image for Logstash which means it'll likely be well supported and maintained for a while.

Logstash is licensed under Apache 2.0.

There is a rich repository of plugins available categorized as inputs, codecs, filters and outputs.

No dependencies, it's a single .jar file. It's written in JRuby and only requires Java to be installed.

Logstash is commonly used as part of ELK stack, that also includes ElasticSearch (a clustered search and storage system) and Kibana (a web frontend for ElasticSearch).

Logstash is built to fit in your stack.

Filters, also known as "groks", are used to query a log stream. They are provided in a configuration file, that also configures source stream and output streams. Since they are stored in a file, they can be under version control and changes can be reviewed (for example, as part of a Git pull request).

There is a cloud based managed version if you are prepared to pay a few bucks.

You can run on mediocre system without problems