Netflix recently introduced Hollow , a Java library and toolkit designed to efficiently cache datasets not characterized as “big data.” Such datasets may be metadata for e-commerce and search engines, or in the case of Netflix, metadata about movies and TV shows. Traditional solutions for processing such datasets include the use of a datastore or serialization, but typically suffer from reliability and latency issues. Hollow’s getting started guide summarizes the core concepts and nomenclature:
Hollow manages datasets which are built by a single producer , and disseminated to one or many consumers for read-only access. A dataset changes over time. The timeline for a changing dataset can be broken down into discrete data states , each of which is a complete snapshot of the data at a particular point in time.
The producer and the consumers handle datasets via a state engine that is transitioned between data states. A producer uses a write state engine and a consumer uses a read state engine.
