Developers are asking NoSQL or SQL what is best for my application? Get answers to the three most important factors to help you decide.
There is no hard and fast rule on when to use a SQL database versus when to use a NoSQL database. Instead, determining your cloud data storage components requires taking a deep dive into the data you’ll be reading, writing, and storing. Answering the questions NoSQL or SQL what is best for my application will take several steps.
But you also need to consider what you need your data to do for you. As the expectations for data processing continue to increase, SQL databases are struggling to keep up. That’s why you’re likely to hear more about NoSQL and its capabilities.
To answer the question of what is best for my application, you need to evaluate several factors. We’ll walk you through these factors and explain how they could impact your decision between SQL and NoSQL.
The most important consideration when evaluating which is best SQL or NoSQL is in evaluating your data’s structure.
When most of your data is structured, you should use a SQL database. Applications that run transactions such as e-commerce platforms, CRMs, and accounting systems lend themselves to SQL well.
Once you understand your data’s structure, you need to move on to evaluating your need for data queries. But the question isn’t just whether you need to query data, but how fast you need those queries to execute and who is responsible for executing such queries.
Due to the structure within SQL databases, you can query data with great ease. Although tedious, the SQL language has been around for decades. The language is mature and has plenty of resources to support it.
As a result, SQL databases are incredibly easy to query and get data back from quickly. The language is lightweight, and although tedious, it’s easy to learn.
Because NoSQL is flexible and lacks that tidy organized structure, querying the data can present some challenges. It’s certainly possible to query these databases, but it isn’t as efficient and takes a bit more expertise.
Developers that created the concept for NoSQL were seeking out flexible, scalable solutions. Their goal was not to find an efficient query structure.
The result of the flexibility and scalability of NoSQL is that you’ll need to undergo more data processing to complete a query. Some developers build in the ability to query their data within the application layer instead of the database layer to simplify the process.
But as NoSQL becomes more popular, many developers and data scientists are skilled at efficiently querying the data. Deciding how and how often to query your data will answer the question should I use SQL or NoSQL?
SQL and NoSQL databases scale differently. So before you build out your application, consider your growth needs. How will your data expand and transform in the future of your application?
SQL databases only scale vertically, which means you need to keep all your data on one server and upgrade the server to meet your needs. That means increasing RAM, SSD, or CPU to accommodate changes. Protecting the integrity of your data means keeping it all on one server.
However, NoSQL databases can scale horizontally, which means you can add additional servers to meet your growing needs. The ability to scale horizontally is one of the greatest strengths of a NoSQL database compared to a SQL database.
NoSQL can scale so well because of its lack of structured data. Each object within the database is independent, meaning the objects can be in different server locations and don’t need to be linked for the database to function. But SQL data is organized in rows and columns that rely on one another for their relational data.
The best way to determine your scaling needs for your database is to evaluate your business goals. And when you do this, don’t look a couple of years in the future, but as far as you possibly can because changing databases for your application will be a timely and costly initiative.
As NoSQL databases develop and mature, they’re blurring the lines between NoSQL and SQL. Remember that NoSQL stands for not only SQL. That means that some data within these databases can be structured.
Many NoSQL databases now offer a convergence of structured and unstructured data. For example, many developers now look at MongoDB SQL or NoSQL because you have options now even once you select a database partner. Many NoSQL databases can now offer ACID transactions to meet your needs.
BangDB offers a multi-model approach to data and layers in AI to make data easier to query. Machine learning is transforming NoSQL databases to make them more intelligent and simpler to operate.
Many applications that could only run on SQL databases before can now transition to NoSQL thanks to the power of artificial intelligence.
The question today is less about SQL vs. NoSQL and more about evaluating which NoSQL database is right for your application. That’s because, given the trajectory of data logging, SQL databases cannot house the amount of ever-growing data efficiently. Very few applications require SQL databases today thanks to new developments and innovations in the NoSQL marketplace.
Data integrity within NoSQL continues to improve but is one area where SQL reigns supreme. However, NoSQL is far more flexible, scalable, and poised for rapid iteration and development.
Still asking the question: NoSQL or SQL what is best for my application? Contact our team to learn more about what the BangDB database can do.