Interpreting the basic idea leads us to realize the benefits of using a variety of appropriate data models for different parts of the persistence layer, the layer being part of the larger software architecture.Īccording to this, one might, for example, use a relational database to persist structured, tabular data a document store for unstructured, object-like data a key/value store for a hash table and a graph database for highly linked referential data. It leads to performance advantages to ArangoDB in comparison to the “layered” approaches.
In ArangoDB, there is no “switching” between data models, and there is no shifting of data from A to B to execute queries. With ArangoDB, the same core with the same query language, one can club together different data models and features in a single query, as we have already stated in previous section. Many database vendors call their product “multi-model,” but adding a graph layer to a key/value or document store does not qualify as native multi-model. In this section, we will highlight a crucial difference between native and layered multimodel databases. And, owing to its multi-model style, one can make lean applications, which will be scalable horizontally with any or all of the three data models. Moreover, different models can be combined in a single query. And with a single declarative query language, any or all of your data can be accessed. In this database, the data can be stored as documents, key/value pairs or graphs.
ArangoDB is hailed as a native multi-model database by its developers.
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