Dremio vs Stroom: What are the differences?
Dremio: Self-service data for everyone. It is a data-as-a-service platform that empowers users to discover, curate, accelerate, and share any data at any time, regardless of location, volume, or structure. Modern data is managed by a wide range of technologies, including relational databases, NoSQL datastores, file systems, Hadoop, and others; 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.
Dremio and Stroom belong to "Big Data Tools" category of the tech stack.
Some of the features offered by Dremio are:
- Democratize all your data
- Make your data engineers more productive
- Accelerate your favorite tools
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.
