doc/modules/cassandra/pages/data_modeling/data_modeling_conceptual.adoc - cassandra - Git at Google

 = Conceptual Data Modeling

 First, let’s create a simple domain model that is easy to understand in
 the relational world, and then see how you might map it from a
 relational to a distributed hashtable model in Cassandra.

 Let's use an example that is complex enough to show the various data
 structures and design patterns, but not something that will bog you down
 with details. Also, a domain that’s familiar to everyone will allow you
 to concentrate on how to work with Cassandra, not on what the
 application domain is all about.

 For example, let's use a domain that is easily understood and that
 everyone can relate to: making hotel reservations.

 The conceptual domain includes hotels, guests that stay in the hotels, a
 collection of rooms for each hotel, the rates and availability of those
 rooms, and a record of reservations booked for guests. Hotels typically
 also maintain a collection of “points of interest,” which are parks,
 museums, shopping galleries, monuments, or other places near the hotel
 that guests might want to visit during their stay. Both hotels and
 points of interest need to maintain geolocation data so that they can be
 found on maps for mashups, and to calculate distances.

 The conceptual domain is depicted below using the entity–relationship
 model popularized by Peter Chen. This simple diagram represents the
 entities in the domain with rectangles, and attributes of those entities
 with ovals. Attributes that represent unique identifiers for items are
 underlined. Relationships between entities are represented as diamonds,
 and the connectors between the relationship and each entity show the
 multiplicity of the connection.

 image::data_modeling_hotel_erd.png[image]

 Obviously, in the real world, there would be many more considerations
 and much more complexity. For example, hotel rates are notoriously
 dynamic, and calculating them involves a wide array of factors. Here
 you’re defining something complex enough to be interesting and touch on
 the important points, but simple enough to maintain the focus on
 learning Cassandra.

 _Material adapted from Cassandra, The Definitive Guide. Published by
 O'Reilly Media, Inc. Copyright © 2020 Jeff Carpenter, Eben Hewitt. All
 rights reserved. Used with permission._
	= Conceptual Data Modeling

	First, let’s create a simple domain model that is easy to understand in
	the relational world, and then see how you might map it from a
	relational to a distributed hashtable model in Cassandra.

	Let's use an example that is complex enough to show the various data
	structures and design patterns, but not something that will bog you down
	with details. Also, a domain that’s familiar to everyone will allow you
	to concentrate on how to work with Cassandra, not on what the
	application domain is all about.

	For example, let's use a domain that is easily understood and that
	everyone can relate to: making hotel reservations.

	The conceptual domain includes hotels, guests that stay in the hotels, a
	collection of rooms for each hotel, the rates and availability of those
	rooms, and a record of reservations booked for guests. Hotels typically
	also maintain a collection of “points of interest,” which are parks,
	museums, shopping galleries, monuments, or other places near the hotel
	that guests might want to visit during their stay. Both hotels and
	points of interest need to maintain geolocation data so that they can be
	found on maps for mashups, and to calculate distances.

	The conceptual domain is depicted below using the entity–relationship
	model popularized by Peter Chen. This simple diagram represents the
	entities in the domain with rectangles, and attributes of those entities
	with ovals. Attributes that represent unique identifiers for items are
	underlined. Relationships between entities are represented as diamonds,
	and the connectors between the relationship and each entity show the
	multiplicity of the connection.

	image::data_modeling_hotel_erd.png[image]

	Obviously, in the real world, there would be many more considerations
	and much more complexity. For example, hotel rates are notoriously
	dynamic, and calculating them involves a wide array of factors. Here
	you’re defining something complex enough to be interesting and touch on
	the important points, but simple enough to maintain the focus on
	learning Cassandra.

	_Material adapted from Cassandra, The Definitive Guide. Published by
	O'Reilly Media, Inc. Copyright © 2020 Jeff Carpenter, Eben Hewitt. All
	rights reserved. Used with permission._