Before starting, we have to discuss the differences between SQL and NoSQL. If you have data with schema-like ID, name, address and the address is a complicated object, store it in a separate table. The ID for one address corresponds to the other table with address ID. This will have the location, city, and state for some sort of foreign key that how we store data in SQL. Now if we store this in NoSQL, the ID, name, and address are all stored in a single JSON document where the address will have an object that stores location, city, and state.

For NoSQL, if an API request comes for an ID, only a single document is traversing. In the case of SQL, the address stored in the other table will be pulled after using other built in method like join. NoSQL doesn’t care about schema, so the schema is flexible in NoSQL but in SQL schema should be predefined.

NoSQL database has inbuilt horizontal partitioning and sharding so they have lot of scale. It is more focused on availability. It has the advantage of built for scale. NoSQL databases are built for finding metrics and getting intelligent data so they are built for aggregations.

NoSQL databases have disadvantages.

These types of databases don’t support too many updates so it may create consistency problems. It doesn’t like SQL database which follows ACID property. This means ACID is not guaranteed and that is the reason why financial systems doesn’t use NoSQL database for their transactions.

The second problem, these databases are not very optimized because the read operation reads the entire block each time to find or match any field of database. It is hard to maintain relation. It doesn’t have any inbuilt function to join two or more collections, so the joins are hard. Joins are all manual in the noSQL database. There isn’t intelligence behind any kind of join we can try to improve. There is only so much we can do because SQL databases are built for join. Inner join, outer join, left join and right join have inherent relationships.

When do we use a NoSQL database?

It depends on if your data is blocked, the number of data updates, what kind of optimization your data needs, and/or the availability of data. Most companies like YouTube and StakeOverflow don’t use NoSQL databases. Databases based on NoSQL are MongoDB, Cassandra, and CouchDB.

The difference between SQL and NoSQL:

1. Maturity: SQL has larger community than NoSQL Community.
2. Dynamic schema: As mentioned, NoSQL gives you flexibility to change your data schema without modifying any of your existing data.
3. Scalability: NoSQL is horizontally scalable which helps reduce the workload and scale your business with ease.
4. Speed: NoSQL has high-performance for simple queries.
5. Flexibility: You can add new columns or fields on NoSQL without affecting existing rows or application performance.
6. Sharding: SQL has no capability of sharding.

Which Database Is Right For Your Organization?

SQL is a strong choice for any organization that has its pre-defined structure and set schemas. Good examples of this are multi-row transaction applications and accounting systems.

Whereas on the other hand, NoSQL is a good choice for companies that are growing or have databases with no pre-defined schema definitions. Some examples of this are mobile applications and real time applications.

If you would like more information, contact Dignitas Digital in Philadelphia by sending an email to hello@dignitas.digital.