This workshop is a con tinuation of the Sunday afternoon tutorial by the same instructors. Attenda nce at the Sunday tutorial is highly recommended for all students consideri ng attendance at this hands-on session.
\nRelational data model ing has several weaknesses. It shreds the data in a business entity into mu ltiple tables. Queries and views must be used to reconstitute business entities, and this slows performance and complicates development because n ormalized data does not match the business-defined objects in applications. Sparse data is hard to represent in relational models. Complex relationshi ps (such as networks and hierarchies of data) are hard to represent and are slow to query. Search is difficult because data is shredded into tables de liberately to remove context.
\nDocument modeling combined with graph modeling solves these problems and creates a powerful new data modeling pa radigm. A document naturally represents a business entity with all its core one-to-many and many-to-many relationships embedded in the document. This greatly speeds query performance and simplifies development because the dat a in the database directly matches the business-defined objects in applicat ions.
\nJSON is the core data model of web services, and JSON is a do cument model. Document databases can directly store and retrieve JSON witho ut modification, which makes web services very easy to develop. Document mo deling by itself is insufficient, though, because we still need to express relationships between business entities.
\nGraph modeling enables doc uments (i.e. business entities) to be related to each other and to transact ion entities. The graph model turns relationships into explicit data (as op posed to implicit foreign keys in the relational model). This makes the rel ationships themselves queryable, and it makes it possible to query for patt erns in the relationships, such as "A mother of a father is a grandmot her, and so is the mother of a mother." It also enables your code to t raverse graphs to find complex patterns and make complex decisions quickly.
\nCombining document modeling with graph modeling creates a document -graph model. This is similar to a property graph model, except that it is much more powerful. A property-graph model is limited to relating a flat li st of properties in one entity to a flat list of properties in another enti ty. The problem is that a business entity is too complex to be represented as a flat list of properties. The document-graph model enables you to conne ct true business entities to each other and to their transactions in any wa y imaginable. This class will show you how to do document-graph modeling. S everal databases make this document-graph modeling possible including Oracl e, Cassandra, MarkLogic, and OrientDB. You can also combine different datab ases to make this possible, such as combining MongoDB and Neo4J.
\n DTSTART:20180423T133000 SUMMARY:Data Modeling for Document and Graph NoSQL Databases: Part 2 - Hand s-On DTEND:20180423T164459 LOCATION: See Description END:VEVENT END:VCALENDAR