DS 4100 Day 13

Today we're talking a bit about NoSQL databases. These databases can be divided into four generes:

Key-Value

Key-Value (KV) databases such as Redis and Riak are the simplest kind of database in which keys are stored with matching values.
A KV-DB is essentially a lookup table that often uses hashing to speed up retrieval.
KV-DBs scale easily and have high performance.
In fact, a file system could be looked at as a key-value data store where the path is the key and the file content is the value.

Columnar databases, such as HBase, are similar to key-value databases in that they store keys with information.
However, rather than storing a single value, a columnar database stores multiple pieces of information – similar to a record.
Unlike a relational database the columns do not have to be of the same data type.
Unlike relational schemas, column-based stores do not require a pre-structured table.
Each record is comprised of one or more columns containing the information and each column of each record can be different.
Columnar databases allow very large and un-structured data to be managed.
They are generally used when simple key-value pairs are not sufficient and storing many records with large amounts of information is a required.

Document databases such as MongoDB and CouchDB are very similar to columnar databases but allow for much deeper nesting of information.
They are ideal for structured documents.
Performance is often an issue with these databases.
XML Stores are an example of a document database.
Document databases often use JavaScript as the native query language with data being exchanged between the client and the server using JSON object.

Graph databases such as Neo4J use “graphs” with nodes and edges connecting each other through relationships.
These databases are ideal in situations where “networks” or “deep connection” must be tracked, such as social networks.

The rest of the class we're working on our new assignment