NoSQL databases (aka non-relational databases) come with both advantages and disadvantages. On the plus side, they are more scalable than traditional relational databases and can store a variety of formats. Additionally, they are easy to use, and their flexibility can speed up development, especially in a cloud computing environment. NoSQL databases were developed as a solution to the restrictions built into traditional relational database technology.
The Advantages of NoSQL Databases
NoSQL databases became popular because they provided a simple way to store data from multiple sources while using different formats. Fewer (or no) transformations are needed when the data is being stored or retrieved from storage. A large variety of data types, whether unstructured, structured, or semi-structured, can be stored in a NoSQL database.
NoSQL databases were developed with the internet and cloud computing as support systems, making it possible to develop a scale-out architecture. Scalability was created by spreading out the data storage and computing processes over a cluster of computers. Increasing capacity required adding more computers to the cluster.
Also, the schemas of several NoSQL databases are quite flexible and can be controlled by the developers. This makes it easier to modify the database for new forms of data. Each specific version of NoSQL databases has different strengths, but all of them share certain basic properties:
- Can support easy updates to schemas
- Can process large volumes of data at high speed
- Storage is scalable
- Can store structured, semi-structured, and unstructured data
These properties provide users with advantages that are not offered by relational databases.
Most NoSQL databases have developed a strong community of users willing to share their experiences and solutions. They can be a very helpful resource in terms of historically shared information and presenting new problems to a group of people interested in helping. These communities are often the fastest, most efficient way of finding a solution.
Another very useful advantage of NoSQL is that it is developer-friendly. The general use and acceptance of NoSQL databases has been based primarily on developers who discovered they could develop and modify specific applications fairly easily using NoSQL. Document databases can use JSON to transform data into a code-like format, in turn allowing the developer to control the structure of the data more easily.
Because NoSQL databases can store data in their native formats, developers aren’t required to adapt the data for storage purposes. By storing data “as it is,” a front-end ETL process is no longer necessary to modify semi-structured data so it can be placed in the row and column formats supported by SQL. This also means fewer applications need to be developed (or purchased) when launching a new database.
The Disadvantages of NoSQL Databases
But NoSQL databases also have their own limitations and weaknesses. The lack of structure can make data untrustworthy and difficult to organize. Common complaints are listed below:
The lack of SQL: The consistent complaint about NoSQL is that it doesn’t come with SQL. SQL is a mature technology, designed for organizing data, while NoSQL is not. Analysts are completely familiar with SQL, and use it on a regular basis. NoSQL was initially designed for researching massive amounts of disorganized, stored data, collected from multiple sources.
The lack of standardization: Each brand of NoSQL database uses its own unique schema. In some cases (such as MongoDB), there is no schema. In other situations (such as Elasticsearch), it is dynamic. In still other designs, it resembles relational databases (for example, Cassandra). The problem here is that each unique system has its own strengths and weaknesses, which must be learned before choosing the right NoSQL database for the situation at hand.
The lack of ACID: ACID stands for the four key properties that define a transaction (Atomicity, Consistency, Isolation, and Durability) and NoSQL does not support these properties.
- Atomicity: This feature represents an all-or-nothing philosophy. For example, money is transferred from Bob’s savings account to his checking account. The process consists of two separate operations, withdrawing money from the savings account and depositing it to the checking account. If a problem occurs in one operation, the entire process stops and the accounts return to their previous balances. This feature can be applied to other situations and when using multiple operations.
- Consistency: Consistency in a database means the data must be valid according to the database’s defined rules. For instance, in an application that transfers money from one account to another, consistency ensures the amount of money, the balance, is correct at the start of the transaction and at the end.
- Isolation: Isolation dictates when and how changes that have been made to an operation become visible to other parallel operations. It also deals with the completeness and consistency of retrieved data. Another aspect of isolation is the goal of allowing multiple transactions to occur simultaneously, without any of the transactions degrading or conflicting with one another.
- Durability: This feature assures transactions are permanently saved and will not disappear accidentally or get erased, even after a database crash. It is normally supported by storing all transactions in a “safe” storage medium.
The absence of these properties makes the data stored in a NoSQL database less trustworthy than those stored in SQL databases.
The lack of JOINs: SQL uses JOINs to establish connections between database tables by matching columns, in turn creating a relationship between those tables. Most of the complex queries used in an SQL database involve join commands. In essence, a join condition helps to combine the data of two or more database tables. These tables are associated through the use of a primary key, as well as foreign keys.
Is NoSQL Worth Using?
NoSQL is absolutely worth using, providing the circumstances are appropriate. Each NoSQL database was developed to resolve specific problems. Using a hammer with screws, or a screwdriver with nails, tends not to work very well. NoSQL databases provide abilities that traditional relational databases cannot. They are useful for handling large amounts of data for research and development purposes and should be selected based on the needs of the organization and the project.
There are many free, open-source NoSQL software programs. There are also many businesses/websites offering a minimal, free, open-source NoSQL program with upgraded, paid versions that are also available. Free can be an excellent reason for using software for research and development purposes.
NoSQL databases also provide faster development. Frequent updates to the data structure in a “relational database” will slow down the research. However, with a NoSQL database, because there is no need to prepare the data ahead of time, frequent updates can be made with minimal downtime.
The Future of NoSQL
NoSQL is not going to replace SQL. SQL is simply too useful for organizing data. NoSQL might fade away as alternative storage and research solutions are developed, but at present, it is still a very useful, easy-to-use research and development tool, and, for the most part, various versions are available for free.
There is the possibility data lakehouses may replace NoSQL software. They typically store data in its original format and use a query engine that transforms the data into a SQL format as it is pulled from storage. The type of cloud storage normally used for data lakehouses is called object storage, which is both cheap and reliable. However, they are a fairly new concept, and can be difficult to set up. The data lakehouse is still in the early stages of its evolution, and it may be a few years before it becomes reasonably priced and easy to set up.
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