SQL vs NoSQL Databases: What’s The Difference?
What is SQL?
SQL (Structured Query Language) is a programming language that is used to manage data in relational databases. Relational databases use relations (typically called tables) to store data and then match that data by using common characteristics within the dataset. Some common relational database management systems that use SQL are Oracle, Sybase, Microsoft SQL Server, Access, and Ingres.
Cobb’s breakthrough paper describes a database where objects could be constructed and queried using something he called SQL, structured query language. He used SQL to create both data (in objects called tables) and the schema for that data, which describes fields in columns. A single record in a SQL database is called a row.
What is NoSQL?
A NoSQL database, on the other hand, is self-describing, so does not require a schema. Nor does it enforce relations between tables in all cases. All its documents are JSON documents, which are complete entities that one can readily read and understand. NoSQL refers to high-performance, non-relational databases that utilize a wide variety of data models. These databases are highly recognized for their ease-of-use, scalable performance, strong resilience, and wide availability. NoSQL database examples include MongoDB, MarkLogic, Couchbase, CloudDB, and Amazon’s Dynamo DB.
Major Differences
There are many differences between SQL and NoSQL, all of which are important to understand when making a decision about what might be the best data management system for your organization. These include differences in:
- Language
- Scalability
- Community
- Structure
The Language
One of the major differences between SQL relational and NoSQL non-relational databases is the language. As mentioned, SQL databases use Structured Query Language for defining and manipulating data. This allows SQL to be extremely versatile and widely-used — however, it also makes it more restrictive. SQL requires that you use predefined schemas to determine the structure of your data before you even begin to work with it. Your data must also follow the same structure as well, which can entail significant upfront preparation along with careful execution.
A NoSQL database features a dynamic schema for unstructured data and the data can be stored in many different ways, whether it be graph-based, document-oriented, column-oriented, or organized as a KeyValue store. This extreme flexibility allows you to create documents without first having to carefully plan and define their structure, add fields as you go, and vary the syntax from database to database. It also allows you to give each document its own unique structure, providing you with more freedom overall.
Efficiency and Normalization
One thing that Oracle stressed was the relationship between objects. They said that all data should be normalized. This means no data should be stored twice. So instead of putting, for example, the school address in every student record, it would be better to maintain a school table and store the address there. NoSQL databases have gotten rid of this constraint, to a certain degree.
Disk space was expensive in the 1970s and so was memory, so normalization made sense. But it can take some time to do a joint operation to bring together a record that is stored in different tables into one logical unit. It also requires the overhead of maintaining index files and writing to those as data is added or deleted
NoSQL databases say all that does not matter as disk space and memory are cheap. Proponents of that say it is okay to, regarding the aforementioned case, put the school address in with the student. This speeds data retrieval time and makes coding easier.
Conclusion
No matter what field you are in, choosing the correct database for your organization is an important decision. NoSQL databases are quickly becoming a major part of the database landscape today, and they are proving to be a real game-changer in the IT arena. They have numerous benefits, including lower cost, open-source availability, and easier scalability, which makes NoSQL an appealing option for anyone thinking about integrating in Big Data. They are a young technology, however, which makes them slightly more volatile.
On the other hand, SQL databases have proven themselves for over 40 years and use long-established standards that are well defined. They have a huge community of experts behind them, and the opportunity for collaboration is limitless.
Overall, the decision of using SQL versus NoSQL for business is not entirely black and white; it requires some comparing and contrasting to determine which database best fits your specific needs. With the proper amount of research and preparation, however, you will ensure that the database you choose provides an efficient and streamlined management system for your organization.