Logstash vs Stroom

Logstash vs Stroom: What are the differences?

What is Logstash? Collect, Parse, & Enrich Data. Logstash is a tool for managing events and logs. You can use it to collect logs, parse them, and store them for later use (like, for searching). If you store them in Elasticsearch, you can view and analyze them with Kibana.

What is Stroom? A scalable data storage, processing and analysis platform. It is a data processing, storage and analysis platform. It is scalable - just add more CPUs / servers for greater throughput. It is suitable for processing high volume data such as system logs, to provide valuable insights into IT performance and usage.

Logstash and Stroom are primarily classified as "Log Management" and "Big Data" tools respectively.

Some of the features offered by Logstash are:

• Centralize data processing of all types
• Normalize varying schema and formats
• Quickly extend to custom log formats

On the other hand, Stroom provides the following key features:

• Receive and store large volumes of data such as native format logs. Ingested data is always available in its raw form
• Create sequences of XSL and text operations, in order to normalise or export data in any format. It is possible to enrich data using lookups and reference data
• Easily add new data formats and debug the transformations if they don't work as expected

Logstash and Stroom are both open source tools. It seems that Logstash with 11K GitHub stars and 2.92K forks on GitHub has more adoption than Stroom with 294 GitHub stars and 32 GitHub forks.