Databases Reference
In-Depth Information
By following this approach our product data model will look like below:
Product Id = “001”,ProductName=”Kelogg Cereal”,
Category=[{Category Id:"NT1",CategoryDesc:"Cereal"}],
Packaging=[{Packaging ID="BX1", Packaging Desc:”Box-24 inches-Rectangular”}]
Key-Value Store
Examples: Membase, Redis
Typical usages: Distributed hash table, caching
Key-Value store behaves like hash tables where the values are mapped to keys. The
simplicity of this model allows storage and processing of any type of information, thus
creating a schema-less storage. Whenever the business application needs excessive read
operations or search type of interactions with data, this model is recommended.
Graph Databases
Examples: Neo4J, InfoGrid
Typical usages: Social networking, recommendations
The Graph Data model is based on Graph theory where data is stored in nodes,
and the linkages to other data are reflected through the edges. This data model is
recommended when the business application does a lot of recursive analysis.
By following this approach our product data model will look like below:
Node: Product
Property: Product ID, Product name, category, and packaging
Relationship: Each product is mapped to a category, and each product has a
packaging specification.
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Relational data modeling is based on the design-themed question, “What answers
do i have from the available data?” This means you must develop applications and formulate
queries based on the data structures and available data. Whereas, no sQl data modeling is
based on the design-themed question: “What questions do i have?” This means, irrespective
of data structures, you design applications with specific questions in mind.
Note
What is JSON
JSON (stands for JavaScript Object Notation) is a lightweight and highly portable
data-interchange format. JSON is intuitive to the Web as well as the browser.
Interoperability with any/all platforms in the current market can be easily achieved
using JSON message format.
