NoSQLIntroductionNoSQL vs NoSQLNoSQL databases are document oriented. Instead

NoSQLIntroductionNoSQL stands for Not only SQL. It differs from SQL (Structured Query Language) in the way data is stored and accessed. SQL is a structured database management system, where data is stored in a well defined schema and tables.

It is also referred to as relational database. On the other hand, NoSQL is an unstructured, non relational database.SQL vs NoSQLNoSQL databases are document oriented. Instead of using a schema and tables, data is instead stored in documents. This is useful for cases where the information available to us is not easily categorized or highly unstructured, such as articles, photos, social media data, videos, or content within a blog post.

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Here a non relational database is better suited as it is more intuitive.Types of NoSQL DatabasesKey-Value model: It is the least complex NoSQL option which stores data in a schema-less way with indexed keys and values. Example- Cassandra, Azure, LevelDB, RiakColumn store (or Wide-Column store): Stores data as columns instead of rows. This can also be viewed as just an inverted table, the advantage being that sectioning out columns allows for excellent scalability and high performance. Example- HBase, BigTable, HyperTableDocument database: Adding more complexity to the key-value concept, each document has its own data and a unique key. It is a good choice for storing retrieving and managing data that is document oriented and semi structured.

Examples- MongoDB, CouchDB Graph: Data that is interconnected can be stored as a graph. This method is capable of high orders of complexity. Example- Polyglot, Neo4J Data in NoSQLData can be stored in a single document that is easily accessed but not necessarily categorized into fields like a relational database does. This does increase processing effort over traditional relational databases. Also, more storage is needed in comparison to highly structured nature of relational database system.AdvantagesAnother very useful of aspect of NoSQL over SQL is integration into OOP language environments like Java, PHP and Python with the use of API’s to execute queries. This makes it possible to access the database without learning SQL or understanding the architecture of underlying database system.DisadvantagesNoSQL is not ACID Compliant (Atomicity, Consistency, Isolation, Durability) which opens it up to anomalies and there is no prescribed way of how transactions interact with the database.

This can lead to leaving the integrity of the database vulnerable. This sacrifice, however, helps in NoSQL achieve higher flexibility and processing speed.When to use NoSQLNo one database system can serve the purpose for every needs.

Hence it is important to know where and when NoSQL can actually be used. Storing large volumes of unstructured data: NoSQL allows addition of different types of data as needs change, and hence is good choice for startups or companies expecting rapid growth and changes in their database needsUtilising cloud storage and computing to the maximum: Cloud-based storage an excellent cost saving solution but needs data to be spread across multiple servers to scale up. NoSQL databases like Cassandra are designed to be scaled across multiple data centres.Rapid Developments: When frequent updates are made to the data structure, or working with quick iterations and downtime between versions is to be minimized, relational databases will cause development to be slowed down. NoSQL data on the other hand doesn’t need to be prepped ahead of time.

ExamplesPopular NoSQL databases include MongoDB, an open-source document database, CouchDB, which uses JSON for documents, JavaScript for MapReduce queries, and regular HTTP for an API. Neo4J is an open source database system with high performance and enterprise-grade graph database. Cassandra provides high scalability and availability without compromising performance. Redis is a data structure server where keys contain strings, hashes, lists, sets and sorted sets.Bibliography


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