what type of database is suitable for projects that do not contain sql?

When working on a project, selecting the most suitable database can be essential for success. For projects that do not contain SQL (Structured Query Language), there are several database options to consider.

NoSQL or Not only SQL is an increasingly popular choice for projects without SQL. This database is designed to handle large volumes of structured, semi-structured and unstructured data. In NoSQL, data is stored using a "key-value" approach, where the data is stored based on relationships between elements and key values. NoSQL databases are often preferred because they can scale up more quickly than those with SQL and are more tolerant of changes in data structure. The most popular example of this type of database is MongoDB.

The JSON Database type (JavaScript Object Notation) also provides an option when working with projects that do not contain SQL. At its core, JSON databases store data as JavaScript objects, which makes them much easier to parse and read than traditional databases. They are ideal for storing web applications and dynamic webpages as they are more flexible than relational databases due to their ability to store unstructured and disparate data formats such as arrays, list strings, timestamps and Booleans. Popular JSON database examples include Cloudant and Couch DB .

Graph Databases offer yet another option when working with projects without SQL support. This type of database stores relationships between entities as networks or graphs instead of traditional tables or rows found in relational databases such as MySQL or Oracle Database. Graph databases excel at mapping complex relationships between entities which allows for faster queries in comparison with other types of databases. Some popular examples include Neo4j, GraphNodes and Redis Graph .

Finally, document stores can also be used when working on projects without strict adherence to the SQL language standard. Document Stores allow you to store different types of documents in a single collection called a 'document type'. Documents can be stored as JSON objects or XML files thereby eliminating the need to create tables like those found in a relational database environment such as MySQL or Oracle Database. Popular examples of document stores include Amazon's DynamoDB and MongoDB Atlas .

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