How to choose between NoSQL database and SQL database?

The debate between SQL and NoSQL is nothing more than a comparison between relational databases and non-relational databases. The differences lie in how they are built, what kind of information they store, and how they store the information. Relational databases are structured, while non-relational databases are document-oriented and distributed. For more than four decades, Structured Query Language (SQL) databases have been the dominant data storage mechanism.

Usage increased dramatically in the late 1990s as web applications and open source technologies such as PostgreSQL, MySQL, and SQLite became increasingly popular. Although NoSQL databases have been around since the 1960s, they have gained popularity recently, with popular options such as MongoDB, CouchDB, Redis, and Apache Cassandra. At the end of the day, both SQL and NoSQL do the same thing: store data, but in different ways. Although NoSQL is becoming increasingly popular, it is not a technology that replaces SQL, but an alternative. Some projects are better suited to using SQL databases, while others are geared toward NoSQL. Some projects can use both interchangeably.

1.SQL

Structured Query Language (SQL) is a more structured, rigid way of storing data, like a phone book. For a relational database to be efficient, you have to store data in a very organized way. SQL databases remain popular because they work natively with many older software stacks, including LAMP and Ruby-based stacks. These databases are widely supported and well understood; this can be a big plus if you run into problems.

When it comes to database technology, there is no one-size-fits-all solution. This is why most companies rely on both non-relational and relational databases for different tasks. But in many cases, while NoSQL databases are becoming increasingly popular due to their speed and scalability, highly structured SQL databases are preferred.

Benefits:

ACID (Atomicity, Consistency, Isolation, and Durability) compliance accurately indicates how transactions interact with the database to reduce anomalies and protect the database Integrity. NoSQL databases often offer the advantages of fast processing and flexibility at the expense of ACID compliance.

Your data remains unchanged and structured. If your company isn't experiencing massive growth (which would require more servers) and is only dealing with consistent data, there's probably no reason to use a system designed to support high traffic and numerous data types.

Due to their early availability, these tools come with better support, product suites, and add-ons for managing these databases.

Disadvantages:

The main problem with SQL is scaling as the database gets larger. You find that even though scalability is usually tested in production environments, it's often not as good as with NoSQL databases. Sharding also has considerable problems.

2.NoSQL

If your company is processing large amounts of unstructured data and your data requirements are not clear from the beginning, it may not be possible to develop a relational database with a well-defined schema. . Using a non-relational database allows you to achieve much greater flexibility than traditional databases. Think of a non-relational database as a folder that organizes various types of related information.

Advantages:

The major factor driving the development of NoSQL is big data, which has promoted the popularity of NoSQL databases such as CouchDB, MongoDB, Cassandra and HBase. NoSQL databases ensure that data does not become the bottleneck while all other components of the server-side application are designed to be seamless and fast.

You can store large amounts of data with almost no structure. In addition, NoSQL databases have no restrictions on the data types that can be stored together, and more new types can be added as your requirements change. If you use a document-based database, you can also store the data in one place without having to define the data types in advance.

Cloud-based storage is a great cost-saving solution, but you have to spread your data across multiple servers to scale. NoSQL databases are designed to scale across multiple data centers without much hassle.

You don’t have to prepare NoSQL data in advance. The non-relational nature of NoSQL databases allows you to create databases quickly without the need to develop detailed database models, thus saving you a lot of development time.

Disadvantages:

Due to its short history, the NoSQL community lacks the maturity of the MySQL user base. Although the NoSQL community is growing rapidly, it is difficult to compete with the vast network of experienced end users compared to SQL database management systems such as MySQL.

One of the big problems with NoSQL databases is the lack of reporting tools for performance testing and analysis. With SQL, on the other hand, you can find a host of reporting tools to help prove the effectiveness of your application.

You will face compatibility issues with SQL instructions. In the query language, the new database uses its own characteristics, which are not yet fully compatible with the SQL used in relational databases.

Lack of standardization. There are many NoSQL databases now, but there are still no standards, while relational databases have standards. This lack of standardization in NoSQL can cause problems during the migration process.

in conclusion

Today, NoSQL databases are becoming an important role in the database market. With their many advantages, they could become a real game-changing technology in the enterprise space. Lower cost, easier scalability and open source make NoSQL an attractive option for companies looking to integrate big data.

Even so, NoSQL is still a relatively young technology and does not have the set of standards provided by SQL databases such as MySQL. Some believe NoSQL is the way of the future, others worry about its lack of ACID compliance and standardization. Ultimately, your company's complex business needs and the volume and variety of data used will determine whether to choose SQL or NoSQL.

For better or worse, for most projects, you can have a non-distributed, scalable relational database as the single point of truth in the system. This is an easy way to maintain data consistency and support complex queries.

I hope this article was helpful, but please remember that every project is different and ultimately it’s up to you to understand what best suits your requirements. Whatever the choice, we developers are very good at justifying our technology choices. However, I recommend that you fully consider the risks and advantages before trying new technologies