Apache Fluo is an open source implementation of Percolator (which populates Google's search index) for Apache Accumulo. With Fluo, users can continuously join new data into large existing data sets without reprocessing all data. Unlike batch and streaming frameworks, Fluo offers much lower latency and can operate on extremely large data sets. If interested in trying Fluo, take the Fluo tour. For any questions you may have, contact us.
When combining new data with existing data, Fluo offers reduced latency when compared to batch processing frameworks (e.g Spark, MapReduce).
Incremental updates are implemented using transactions which allow thousands of updates to happen concurrently without corrupting data.
The core Fluo API supports simple, cross-node transactional updates using get/set methods.
Combine new data with existing data without having to reprocess the entire dataset.
Fluo applications consist of a series of observers that execute user code when observed data is updated.
The Fluo Recipes API builds on the core API to offer complex transactional updates.