5 Main Differences Between SQL and NoSQL Databases
In today’s world, many have heard of SQL and NoSQL. However, there is still confusion about when to use each. Let’s begin by defining SQL and NoSQL. Relational database is another name for SQL databases. Non-relational or distributed database is another name for NoSQL databases. Although SQL's are more common, more businesses are continuing to adopt NoSQL databases. To clarify SQL and NoSQL further, we will discuss the main differences between SQL databases and NoSQL databases. We will also provide some examples of each.
They are table-based databases, which means these databases represent that data in rows.
Additionally, SQL databases have a predefined schema and must follow the same structure. As a result, they usually require significant up-front preparation. Therefore, a change in the structure is challenging and can be disruptive to your whole system.
These databases are vertically scalable. Therefore, by increasing your server’s RAM, CPU, or SSD, you can store your SQL database on the same server.
There is a great amount of support available for SQL databases from outside vendors. Some examples of SQL databases include PostgreSQL, MySQL, Oracle, and Microsoft SQL Server.
When you have complex queries, these databases are a good because of the standard interfaces and powerful query language.
To begin, NoSQL databases are document based, which means the data is represented in graphs and wide column stores.
NoSQL databases do not have standard schema definitions that the data has to adhere to. Since the data is stored in many ways, each document can have its own unique structure.
NoSQL databases are horizontally scalable. This means the only way to handle more traffic is to increase the number of servers.
Support for NoSQL is not common, so many times you will have to rely on community support. Some NoSQL database examples include Redis, RavenDB Cassandra, MongoDB, BigTable, HBase, Neo4j and CouchDB.no
NoSQL databases are a good fit for hierarchical data storage. These databases follow the key-value pair way of storing data NoSQL databases. Thus, they are good for large data sets.
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