Unlike a relational database where every record contains the same fields, leaving unused fields empty there are no empty 'fields' in either document (record) in the above example. The structure and text and other data inside the document are usually referred to as the document's content and may be referenced via retrieval or editing methods, (see below). These two documents share some structural elements with one another, but each also has unique elements. For example, the following is a document, encoded in JSON: Document stores are similar in that they allow different types of documents in a single store, allow the fields within them to be optional, and often allow them to be encoded using different encoding systems. Every object, even those of the same class, can look very different. ![]() Generally, programs using objects have many different types of objects, and those objects often have many optional fields. They are not required to adhere to a standard schema, nor will they have all the same sections, slots, parts or keys. Encodings in use include XML, YAML, JSON, as well as binary forms like BSON.ĭocuments in a document store are roughly equivalent to the programming concept of an object. While each document-oriented database implementation differs on the details of this definition, in general, they all assume documents encapsulate and encode data (or information) in some standard format or encoding. The central concept of a document-oriented database is the notion of a document. This eliminates the need for object-relational mapping while loading data into the database. Document databases store all information for a given object in a single instance in the database, and every stored object can be different from every other. Relational databases generally store data in separate tables that are defined by the programmer, and a single object may be spread across several tables. Although the difference is often negligible due to tools in the systems, conceptually the document-store is designed to offer a richer experience with modern programming techniques.ĭocument databases contrast strongly with the traditional relational database (RDB). The difference lies in the way the data is processed in a key-value store, the data is considered to be inherently opaque to the database, whereas a document-oriented system relies on internal structure in the document in order to extract metadata that the database engine uses for further optimization. Graph databases are similar, but add another layer, the relationship, which allows them to link documents for rapid traversal.ĭocument-oriented databases are inherently a subclass of the key-value store, another NoSQL database concept. XML databases are a subclass of document-oriented databases that are optimized to work with XML documents. ![]() ĭocument-oriented databases are one of the main categories of NoSQL databases, and the popularity of the term "document-oriented database" has grown with the use of the term NoSQL itself. ![]()
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