Let’s compare SQL vs. NoSQL databases and review their strengths and weaknesses.
Join the DZone community and get the full member experience. What’s the best way to store, protect, and access your data? This is a fundamental, yet critical decision. After all, data is the cornerstone of success for just about every modern organization. For most companies, the choice comes down to SQL and NoSQL databases. Each has unique strengths and weaknesses. They’re extremely flexible and easy for developers to work with and modify. Learn more about SQL and NoSQL databases and their basic differences. The best choice? Well, it depends on a whole slew of factors, including your querying, availability, and compliance needs, along with your variety of data types and expected growth. Let’s take a close look at the pros and cons of SQL vs. NoSQL to help you make the right choice. While the standardized schema of SQL databases makes them rigid and difficult to modify, it does come with some advantages. All data added to the database must comply with the well-known schema of linked tables made up of rows and columns. Some may find this limiting or confining, but it is helpful when data consistency, integrity, security, and compliance are at a premium. At almost 50 years old, the SQL programming language is extremely mature and still widely used. It has a strong community, with countless experts willing to share tips and well-established best practices. There are many opportunities to sharpen skills and collaborate. If necessary, consultants and SQL vendors can provide additional support. With SQL, your developers will be able to find the answers they need. SQL is a user-friendly language. Managing and querying the database can be accomplished using simple keywords with little to no coding required. Most developers are taught SQL in college. The extremely structured nature of relational database tables enables SQL databases to be Atomicity, Consistency, Isolation, and Durability (ACID) compliant. This level of compliance keeps tables in-sync and guarantees the validity of transactions. It is likely the right choice when you run applications that have no room for error and need the highest level of data integrity. Here are the ACID properties:
The norm for SQL databases is to scale-up vertically, where capacity can only be expanded by increasing capabilities, such as RAM, CPU, and SSD, on the existing server or by migrating to a larger, more expensive one. You’ll need to continually increase hard drive space as your data grows and you’ll need faster machines to run evolving and more sophisticated technologies. The database vendor you use will likely require you to periodically level up your hardware just to run their latest releases. In this environment, hardware can quickly become outdated. Each upgrade is sure to be expensive and resource intensive. SQL’s hardware needs also include ongoing, everyday maintenance and operating costs. It’s a never-ending hamster wheel. Developed at a time when the cost of data storage was high, relational databases attempt to negate data duplication. Each table has different information and they can be connected and queried using common values. However, as SQL databases get large, the lookups and joins required between numerous tables can slow things down. A SQL database’s schema must be defined before use. Once in place, they are inflexible, and modifications are typically difficult and resource-intensive. For that reason, substantial time needs to be invested in upfront planning, before the database is ever put into production.
