Stroom vs LogSense: What are the differences?

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; LogSense: Intelligent log monitoring, analytics and vulnerability discovery. It makes it easy to understand what’s happening in your environment. You can submit any type of log (including web logs, application logs, and system logs) for parsing and analysis. All with no training, no agents, or hassles Our patent-pending machine learning engine can parse all logs – even if the pattern is unknown. Once parsed, unknown logs will be displayed so that the keys can be renamed as desired. All future logs will be recognized with those keys and are available for charting and alerting immediately based on any defined criteria you establish..

Stroom belongs to "Big Data Tools" category of the tech stack, while LogSense can be primarily classified under "Log Management".

Some of the features offered by Stroom are:

• 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

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

• Logs as a service
• Logs collection
• Logs parsing

Stroom is an open source tool with 316 GitHub stars and 33 GitHub forks. Here's a link to Stroom's open source repository on GitHub.