In this case the content of the document may have a different set of properties. For example a directory of user profiles one of them indicate his favorite dish as a preference and the other a video game. Since this information cannot be store in one field due to logical and structural separation they are recorde in separate properties of individual documents. If necessary you can add new properties to documents without violating the overall integrity of the data. Document oriente databases Peculiarities well suite for the rapid development of systems and services that work with differently structure data easily scalable and change the structure if necessary.
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Examples MongoDB RethinkDB CouchDB DocumentDB. Graph databases This family of bases is intende for modeling complex relationships using graph theory where graph eges act as links and the objects themselves are nodes or vertices. Graph bases An example of a graph database structure. This approach can be useful when analyzing the profiles of social El Salvador Email List network users. One user is subscribe to the updates of the second another user is subscribe to a certain community and so on. Also the technology can be use in the analysis of the economic activity of counterparties to identify various fraud schemes.
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For example you can track the use of certain accounts cards or counterparty details in various transactions. Features high performance since traversal of eges and vertices is much faster than analyzing many external and internal tables and BM Leads joining them according to the selection condition in relational databases. Examples Neo J JanusGraph Dgraph OrientDB. Column databases As the name implies records in such databases are store not by rows but by columns columns . Instead of tables column families are use here. They contain keys that indicate the format of the string to record information about the object. Each row has its own set of properties which allows you to store differently structure data within the same family.