![]() In this section, we will highlight a crucial difference between native and layered multimodel databases. 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. 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. In ArangoDB, there is no “switching” between data models, and there is no shifting of data from A to B to execute queries. It leads to performance advantages to ArangoDB in comparison to the “layered” approaches. 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. ![]() ![]() #Nosql arangodb 27.8m capitalsawersventurebeat software# However, traditional implementation of this approach will lead one to use multiple databases in the same project. It can lead to some operational friction (more complicated deployment, more frequent upgrades) as well as data consistency and duplication issues. ![]() The next challenge after unifying the data for the three data models, is to devise and implement a common query language that can allow data administrators to express a variety of queries, such as document queries, key/value lookups, graphy queries, and arbitrary combinations of these.īy graphy queries, we mean queries involving graph-theoretic considerations.
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