When optimizing your operations for either desktop or mobile web development, it’s essential to talk about data organization - especially if you are in a state of rapid growth. Massive amounts of data add up as an app or website scales. Sometimes, that data can be messy: different types, different sources; there are numerous things to consider when running a business that depends heavily on data organization. Oftentimes, in-house databases can not keep up with the load.
As your applications evolve and things change, the solutions you architected before might no longer work. That’s a sign that you might need to change your data pipeline structure to suit your (new) needs.
Many companies choose to outsource their databases to companies like MongoDB and MySQL. Both have competitive and attractive advantages that place them in the tiers of the elite. Here are some considerations you need to factor in before deciding which is the better choice for your business.
Are you interested in optimized mobile development for your business? Contact our team today!
MongoDB vs MySQL Comparison
MongoDB is one of the leading NoSQL cloud-based databases and is a notable leader as a document-oriented operation. It is developed, maintained, and updated by the same corporation, MongoDB Inc. It was released in 2009 and is currently used by organizations like Twitter, T-Mobile, Sony, and InVision.
MongoDB’s flexibility and reliability make it an excellent choice for meeting capacity and speed demands for many companies. It also precludes the need for a fixed structure due to its schema-free implementation. This allows you to specify hierarchical relationships and change the entire record structure without the need for rigid schemas. There are no restrictions on the schema design; you can add documents as needed without specifying a relationship. MongoDB takes care of that for you.
The only requirement is that these documents and related data structures are in a supported format. There is also a wide range of supported operators under the JSON umbrella, and it treats assets as having an implicit AND operator for filtering logic. It also supports OR data queries, but it requires a different operator and grouping the items together in an array.
MongoDB will inevitably experience some slowdown over time as the data volume grows in scope. MongoDB also does not support atomic transactions, instead relying on imputed atomic updates on a single document level. While it is possible to make up for this drawback, there is still a notable detriment to speed. Also, because the solution is relatively new, replacing legacy systems comes with a learning curve, if you can replace them with MongoDB at all.
MySQL has been around longer than MongoDB, as has it’s community. Because of this, MongoDB’s community support and documentation isn’t as robust as MySQL. This can make MongoDB a riskier choice in some situations.
MongoDB has a rich breadth of functions that make it an excellent choice for scaling operations that have suddenly grown too large for some legacy systems to handle. Its resilience is also very useful when it comes to possible failure conditions, such as crashes. It works well for extensive data that is not structured or complex. If you have difficulty defining your schema, MongoDB is a good choice.
Related: Elements of an Innovation Team
MySQL is an open-source (anyone can use it) relational database management system. MySQL has been around since 1995 and is used by giants like Twitter, YouTube, NASA, and PayPal. It uses a traditional format for its data storage, organizing data into rows and tables with nested classifications. It uses SQL to run queries and update data. These relationships and their corresponding logic are stored in discrete tables, but MySQL takes advantage of JOIN executions to ensure that different queries are correlated across many tables. This removes much of the worries regarding data duplication, which can cause a massive headache that will require cleaning.
Do you still have lingering questions about the power of a relational database? Contact our team with your queries!
MySQL’s JOIN operations are truly where it shines; it is what makes a relational database relational in the first place, ensuring that daa is linked across multiple tables. This removes a lot of the worries about replicating data, which can cause significant delays. MySQL also has a more detailed history, meaning its documentation and community is far more developed than MongoDB. It also supports atomic transactions, along with a secure password security system.
These bonuses are the reason it is one of the most popular platforms for businesses that have large data sets of similar types and relationships.
MySQL can quickly turn into a timesuck depending on how often you execute certain operations like incremental backups (which MongoDB takes care of for you). MySQL is also fairly schema-dominant, meaning that much of the flexibility afforded by MongoDB’s schema-less system is erased. It was also designed as a single-node system and not with modern data concepts in mind, which can lead to issues in scalability. This will inevitably lead to lags.
MySQL’s robust computing infrastructure is extremely useful for operations that field a lot of data and rely on security and stability, with its high performance in all metrics being its main strength. It also boasts exceptionally reliable data protection and a simplistic management system that makes organizing your data tables easy and straightforward. However, you need to be mindful of proper data indexing. MySQL works well with companies that have the resources to manage different data types and organize them in a systematic way.
MongoDB vs MySQL: Which database is right for my business?
Both platforms have competitive advantages depending on the scope of your project or your goals for your company. Both solutions serve different purposes.
MySQL maintains binaries for Windows, OS X, Linux, AIX, BSDi, HP-UX, FreeBSD, IRIX, NetBSD, and others. MongoDB has binaries for Linux, Solaris, OS X, and Windows, so there is a slight limitation.
If binary support is not an issue, MySQL (and most relational databases, for that matter) are useful for systems that need to handle multi-row transactions like accounting. Updating multiple tables that take data that updates relationally is easy through MySQL.
MongoDB, however, is very useful for real-time analytics and handling unstructured data of various types. This makes it well-suited for the Internet of Things, mobile applications, uses where the data is coming from all directions, in all different kinds, and of varied size. This is especially useful when you are unsure of what schema you want to define for your database. MongoDB also scales better than MySQL, meaning it can grow and build upon itself where MySQL’s structure prevents it from doing so.
Depending on your unique circumstances, MySQL or MongoDB can both be excellent options for your organization. Choosing a database for your company requires you to consider the type of data you plan on collecting (structured of the same kind, or unstructured data of various types), as well as if you anticipate your operations expanding beyond their current scope.
You need to think in terms of growth, reliability, speed, and scalability. Otherwise, your current infrastructure could be severely backlogged at just the moment that your business is thriving.
Are you still unsure which database is the best choice for your unique needs? Contact our team at SF AppWorks with your query, and we’ll walk you through every step!
Contributor credits: Raul Rene Lepsa