Gravwell vs Stroom: What are the differences?

Gravwell: Ingest everything, compromise nothing. Data analytics at scale with predictive pricing. It is the most flexible full-stack analytics platform in the world. We excel at fusing disparate data sources such as firewall logs, end point event logs, network traffic, OT IDS logs, OT process data, threat feed data, etc. to create a central source of knowledge. Created in the IoT age we know modern data insights demand unlimited ingest and analysis capability for cybersecurity, IoT, business analytics, and more. We support a wide range of customers, from energy production, energy delivery, government, finance, and insurance to health and beauty products; 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.

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

Some of the features offered by Gravwell are:

• Ability for deployment in cloud, on-premises, or in an isolated on-premises network lacking outside network connectivity
• Capable of collecting disparate unstructured time-series data sources into a queryable data lake
• Enable data scientists to create custom analysis code/tools to be executed as part of a search pipeline or query system

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

Stroom is an open source tool with 294 GitHub stars and 32 GitHub forks. Here's a link to Stroom's open source repository on GitHub.