In this podcast episode, I talk multi-model databases with Damon Feldman, solutions director at MarkLogic. If this conversation gets you interested in multi-model databases, be sure to check out his live webcast on December 1, 2016.
“A multi-model database at its basic [level] is really what it sounds like: it’s a database that stores multiple models in terms of how it represents data,” says Feldman. They go beyond classic entity-relationship models to store graphs, JSON documents, triples, and perhaps binary content.
Multi-model databases aren’t necessarily huge installations with many models; Feldman says the most common multi-model installations have three models, though two-model databases are also widespread. “I’m seeing more and more databases start to pick up at least two models,” he says. “Sometimes there’s a model that doesn’t do everything you need to do, and there’s a known gap, so you add one more model.”
Feldman describes the model types most commonly found in multi-model databases:
- Entity-relationship model, like in a SQL database
- Document model, often XML or JSON
- Text model, opting to store text in a database rather than in a different repository that would require integration
- Graph or triple model: RDF or semantic data. Essential when a lot of entities are linked together
- Key-value store: a very simple “black-box” cache
For more on multi-model databases, watch Damon Feldman’s live webcast on December 1, 2016.
This post is a collaboration between O'Reilly and MarkLogic. See our statement of editorial independence.