When do we choose a NoSQL database? Differentiate between SQL and NoSQL databases.Name any SQL and NoSQL tools also

We choose a NoSQL database when we have the following requirements:

1. Large amounts of data: NoSQL databases are designed to handle large volumes of data that may not fit well into a relational model.

2. Scalability: NoSQL databases are designed to expand easily to accommodate more data.

3. Speed: NoSQL databases use mechanisms like sharding to provide fast read and write operations.

4. Flexibility: NoSQL databases allow you to store data in a variety of ways depending on your needs. You can store data as key-value pairs, wide-column stores, graph databases, or document databases.

The main differences between SQL and NoSQL databases are:

1. Structure: SQL databases are table-based, while NoSQL databases can be key-value pairs, wide-column stores, graph databases, or document databases.

2. Scalability: SQL databases are scaled by enhancing the hardware, while NoSQL databases are scaled by increasing the databases servers in the pool of resources to reduce the load.

3. Language: SQL databases use SQL (structured query language) for defining and manipulating the data, which is very powerful. In contrast, NoSQL databases have a dynamic schema for unstructured data, and data is stored in many ways in NoSQL databases, so it can be document-based, column-oriented, graph-based, or organized as a KeyValue store.

Examples of SQL tools include MySQL, Oracle, and SQL Server. Examples of NoSQL tools include MongoDB, Apache Cassandra, and Google Cloud Bigtable.