15 Tips for Getting an Overview of Relational and Non-Relational Databases
15 Tips for Getting an Overview of Relational and Non-Relational Databases
While relational database solutions have been around for many years, non-relational databases are new and emerging, which has triggered a debate on how the two compare. As the subject matter experts over at runrex.com point out, while these two types of databases are very different, they are both equally useful in their own right, for contrasting user-cases and reasons. One type is, therefore, not better than the other, which means that both have their place. This article will look to highlight 15 tips that will give you an overview of what these two are about, their properties, and how they differ from each other.
- Relational databases
Relational databases, also referred to as relational database management systems (RDBMS), or SQL databases, store data in tables and rows, also referred to as records as covered over at guttulus.com. The most popular of these include Microsoft SQL Server, MySQL, IBM, Oracle Database, among others. Except for MySQL, which is mostly used to store data from web applications, RDBMS are mostly used in large enterprise scenarios.
- Non-relational databases
These are also referred to as NoSQL databases, and while they also store data, here there are no tables, rows, primary keys, or foreign keys, unlike in relational databases. Instead, as explained over at runrex.com, non-relational databases use a storage model optimized for specific requirements of the type of data being stored. Popular NoSQL databases include MongoDB, Apache Cassandra, Redis, Apache HBase, among others. NoSQL databases are usually grouped into four categories: Key-value stores, Graph stores, Column stores, and Document stores.
- Structured and non-structured data
As the subject matter experts over at guttulus.com are quick to point out, one of the main differences between these two is the types of data that each works with. Here, while relational databases usually work with structured data, non-relational databases usually work with semi-structured data (JSON, XML).
- Relational databases are complex internally
As highlighted over at runrex.com, relational databases offer simplicity, robustness, flexibility, performance, and compatibility, which is why they have been around for so long. However, to offer all these benefits, they are incredibly complex internally, which is hidden under the hood, with the RBDMS determining the best plan of action to answer requests with the help of algorithms.
- Relational databases and scalability
The main concern for relational databases is when it comes to the scalability of large databases. This is because why relational databases scale well on the main, they only do so when that scaling happens on a single server. Therefore, when you try to scale to many servers, then the complexities become overwhelming. This is why relational databases probably aren’t viable for large distribution systems.
- Non-relational databases offer simplicity in design
As is covered over at guttulus.com, non-relational databases don’t have to deal with the “impedance mismatch” between the object-oriented approach to writing applications and the schema-based tables and rows of relational databases, which means that, as compared to relational databases, they offer simplicity in design.
- Non-relational databases offer better control over availability
As far as non-relational databases are concerned, servers can be added or removed without application downtime from discussions over at runrex.com. This means that most NoSQL databases support data replication, storing multiple copies of data across the cluster or even across data centers, which ensures high availability and disaster recovery.
- Non-relational databases are quicker
As is outlined over at guttulus.com, the data structures used by NoSQL databases are different from those used by default in relational databases, which makes operations in NoSQL faster than in relational databases, particularly since there is no joining of tables. Most NoSQL databases do not even support joins.
- Costs involved
When looking at relational and non-relational databases, you have to consider costs. According to runrex.com, NoSQL databases usually use clusters of cheap commodity servers, while relational databases tend to rely on expensive proprietary servers and storage systems. Additionally, the licenses for relational database systems can be quite expensive as compared to those for NoSQL databases which are open-source and, therefore, free.
- Where are NoSQL databases preferred?
Non-relational databases are increasingly being used in big data and real-time web applications. Since the introduction of the web, when databases went from a maximum of a few hundred users on an internal company application to millions of users on a web application, NoSQL databases have become increasingly popular.
- Reasons that may block the application of NoSQL stores
While it seems like using NoSQL blocks is the way to go, certain things may block its use such as the use of low-level query languages, the lack of standardized interfaces, as well as huge investments in existing SQL. Also, as outlined over at guttulus.com, relational databases are usually much simpler to use as they have GUIs while many NoSQL solutions use a command-line interface.
- Key-value stores and their drawback
Key-value stores in non-relational databases allow you to stores several related items in one “row” of data in the same table, which allows, for example, all data relating to one customer or client to be conveniently stored together as one record as explained over at runrex.com. However, one downside with this is that key-value stores, unlike relational databases, cannot enforce relationships between data items.
- Responsibility for enforcing business logic and rules
As pointed out by the experts over at guttulus.com, in the relational model, there is a built-in and foolproof method of ensuring and enforcing business logic and rule at the database layer, while in key-value stores, this responsibility falls on the application logic. Many people are, therefore, uncomfortable with leaving this key responsibility just to the application, which is one of the reasons why relational databases continue to be used.
- Why NoSQL databases dominate web-applications
When it comes to web-based applications that use databases, rigorously enforcing business logic and rules is usually not a top priority. This is because, from discussions over at runrex.com, the ability to service large numbers of user requests, which are usually read-only queries, is the main priority. This is why NoSQL databases are increasingly being used in web-applications.
- Data warehousing
It is also worth pointing out that relational-model databases can also be tweaked to set up to run large-scale read-only operations through data warehousing. This will allow such models to serve a large number of users who are querying a large amount of data, particularly when using relational MPP architectures such as Teradata, Oracle Exadata, among others.
These are just some of the things to know about as far as an overview of these two is concerned, with more on this very wide topic to be found over at runrex.com and guttulus.com.
