A growing business faces a lot of challenges and opportunities and so it demands a future proof planning. Some tools and technology are the best fit for your application today but the same may not work tomorrow. Picking the right database is also a part of the application which is a challenging decision for the organizations. It shows how well you can architect your application. Suppose you choose a database for your application based on the current scenario and considering the small number of users then what can happen after a couple of years? Users may grow…and if users will grow then you will start facing the scalability issue and several other problems on your website. If your site won’t be able to handle the large volume user growth then it will affect your business badly and your business may fall as well. For the maintenance or migrations of your application, you will have to put more effort, time and money as well.
Well, it has been always an argument among developers that which database is best suitable for the applications…Relational or non-relational? Both databases can store information but the difference lies in how they’re built, the kind of information they store, and how they store it.
In this article, we are going to discuss some scenarios where you can choose non-relational databases over relational databases for your application. We will discuss some features of NoSQL but you need to remember that there is technology or database that fits all. You will find pros and cons for each one of them. So to make a choice, you first need to ask a few questions about the needs of your application. Answering these questions will help you identify the needs of your application and you will be able to find that is NoSQL is the best fit for your application or not.
- Can your application support your projected user volume growth?
- To cope up with user demands/activities. Do you need to scale your applications?
- How much money and time can be saved with 0% downtime?
- Would your application benefit from rapid development cycles? (flexible data model)
- Does your application generate huge amounts of data?
For more than four decades people are using relational databases as a primary data storage mechanism. Structured Query Language (SQL) happens to be the more structured, rigid way of storing data, like a phone book. They are designed for reliable transactions and follow a proper structure to store data in a very organized manner. These databases can handle thousands of queries in just a fraction of seconds but this is possible at the small scale applications. When the application grows relational databases start facing the scalability issue. If we talk about the big gigantic website (such as Facebook, Google, Amazon) that throws billions or trillions of queries within a small amount of time then relational databases get failed in handling the queries. To get rid of this limitation in relational databases NoSQL comes in the picture that mainly focuses on two things…high operations speed and flexibility in storing the data. These two are the main common things that gave birth to the NoSQL database.
NoSQL databases have been around a long time – since the 1960s but the name “NoSQL” was only coined in the early 21st century. If your organization is dealing with massive amounts of unstructured data and your data requirements aren’t clear at the outset, you probably don’t have the luxury of developing a relational database with a clearly defined schema. In these cases use NoSQL databases, you will get much more flexibility than its traditional counterparts. Let’s discuss 5 important features of NoSQL databases. It will give you a clear picture when to use it…
Relational databases store data in a fixed and predefined structure. It means when you start development you will have to define your data schema in terms of tables and columns. You have to change the schema every time the requirements change. This will lead to creating new columns, defining new relations, reflecting the changes in your application, discussing with your database administrators, etc.
NoSQL database provides much more flexibility when it comes to handling data. There is no requirement to specify the schema to start working with the application. Also, the NoSQL database doesn’t put a restriction on the types of data you can store together. It allows you to add more new types as your needs change. These all are the reasons NoSQL is best suited for agile development which requires fast implementation. Developers and architects choose NoSQL to handle data easily for various kinds of agile development application requirements.
2. Easily Scalable
The primary reason to choose a NoSQL database is easy scalability. Well, relational databases can also be scaled but not easily and at a lower cost. Relational databases are built on the concept of traditional master-slave architecture. Scaling up means upgrading your servers by adding more processors, RAM, and hard-disks to your machine to handle more load and increase capacity. You will have to divide the databases into smaller chunks across multiple hardware servers instead of a single large server. This is called sharding which is very complicated in relational databases. Replacing and upgrading your database server machines to accommodate more throughput results in downtime as well. These things become a headache for developers and architects.
NoSQL database built with a masterless, peer-to-peer architecture. Data is partitioned and balanced across multiple nodes in a cluster, and aggregate queries are distributed by default. This allows easy scaling in no time. Just executing a few commands will add the new server to the cluster. This scalability also improves performance, allowing for continuous availability and very high read/write speeds.
Relational databases use a centralized application that is location-dependent (e.g. single location), especially for write operations. On the other hand, the NoSQL database is designed to distribute data on a global scale. It uses multiple locations involving multiple data centers and/or cloud regions for write and read operations. This distributed database has a great advantage with masterclass architecture. You can maintain continuous availability because data is distributed with multiple copies where it needs to be.
4. Redundancy and Zero Downtime
What will happen if the hardware will fail? Well, NoSQL is also designed to handle these kinds of critical situations. Hardware failure is a serious concern while building an application. Rather than requiring developers, DBAs, and operations staff to build their redundant solutions, it can be addressed at the architectural level of the database in NoSQL. If we talk about Cassandra then it uses several heuristics to determine the likelihood of node failure. Riak follows the network partitioning approach (when one or more nodes in a cluster become isolated) and repair itself.
The masterclass architecture of the NoSQL database allows multiple copies of data to be maintained across different nodes. If one node goes down then another node will have a copy of the data for easy and fast access. This leads to zero downtime in the NoSQL database. When one considers the cost of downtime, this is a big deal.
5. Big Data Applications
NoSQL can handle the massive amount of data very quickly and that’s the reason it is best suited for the big data applications. NoSQL databases ensure data doesn’t become the bottleneck when all of the other components of your server-side application are designed to be seamless and fast.
As we have mentioned about many features and advantages of using the NoSQL database but that doesn’t mean that it fits in all kinds of applications. There are some downsides of NoSQL as well so choosing the right database depends on your type of application or nature of data. Some projects are better suited to using an SQL database, while others work well with NoSQL. Some could use both interchangeably.
If you are storing transactional data then SQL is your friend. Relational databases were created to process transactions and they are very good with that. If your data is analytical then think about NoSQL, SQL was never intended for data analytics and with large amounts of data that can become an issue.