At its core, MarkLogic is a multi-model database. MarkLogic provides native storage for JSON, XML, RDF, geospatial, and large binaries (e.g., PDFs, images, videos). With this approach, it is easy to get all of your data in and easy to make changes later on. Load all of your data as is— structured and unstructured data (and your metadata!)— without cumbersome ETL processes. If you need to add another data source or make changes to your schemas later on, go on!
The document database is the most flexible of the NoSQL data models, and the most popular. Documents are ideal for handling varied and complex data. They are human-readable, they closely map to the conceptual or business model of the data, and they avoid the impedance mismatch problem that relational databases have. Whether it’s Java objects that represents business entities or free flowing text from a “document” in the more traditional sense (Microsoft Word documents, PDFs, etc.), they are all naturally stored as JSON and XML documents in MarkLogic.
MarkLogic also has a built-in RDF Triple Store (a type of graph database) for storing and managing semantic data. We call this capability MarkLogic Semantics. Semantics enhances the document model by providing a smart way to connect and enhance the JSON and XML documents that MarkLogic stores, which is important for data integration and more powerful querying.
Learn more about MarkLogic’s Flexible Data Model with the technical resources provided below.