When should you use MongoDB over MySQL and vice versa? One of MySQL's greatest strengths is its widespread usage, especially in web development. It also offers some interesting features in terms of replication and sharding to improve scalability. MySQL is one of the fastest relational databases. One interesting feature is its ability to determine its storage strategy on a per-table basis, allowing for fine-tuning depending on the scenario. MySQL is an open-source relational database engine. Its direct competitors are PostgreSQL and MariaDB. So if you're planning on using it, be ready to set aside large disks for it. The downside is that MongoDB's disk space administration could be better. Another strong point is its thorough documentation. Most operations are optimized to use local RAM, so if the hardware is available and the indexes are properly designed, a MongoDB-based database can be a real asset. One of the outstanding features of MongoDB is its performance. As such, its direct competitors are CouchDB, Cassandra, and HyperTable. MongoDB is an open-source document-oriented database, also referred to as a noSQL database. Now that we have some clarity regarding noSQL databases and SQL databases, we can look at MongoDB vs MySQL. But the cost is the loss of certainty in the quality of the information. The lack of these safety mechanisms give noSQL databases an edge over relational ones in terms of general performance and scalability. That makes it harder to keep those relationships consistent (by avoiding orphans, for instance) and to retrieve related information spread across several collections. In a noSQL database, information is stored in a loose structure, so the properties of two different documents in the same collection can vary significantly.Īnother important difference is that database engines don’t know the relationship between documents in different collections. But it's not. In a relational database, the information structure plays a major role. You might get the impression that this is another way of saying the same thing. While a SQL database has consistent columns, a noSQL database may have different data associated with each record. Instead, noSQL databases have collections, documents, and properties. In a relational database, foreign keys enable you to connect data from one table to another.Īnd having a strong system in place helps prevent some simple inconsistencies within the database.Ī noSQL database doesn't use a relational model. The database itself makes it easy for you to enforce consistency across the model via tools such as foreign keys. You define a data model by putting together a set of tables that contain records with a fixed number of fields that contain a specific data type. ![]() In this model, data is heavily structured. The difference is how the information is organized internally.Ī relational database is based on a relational model. So before we get into the specifics of each product, we need to address the real question: should you use SQL or noSQL? What are the differences between SQL and noSQL databases?īoth SQL and noSQL databases are tools designed to store information. Why? Because MongoDB is a noSQL database, and MySQL is a SQL database. That's like comparing apples to oranges instead of apples to apples. And in order to do that, you need to understand that a straight comparison of MongoDB versus MySQL isn't a fair one. ![]() This article is about the tools you need to make an informed decision about. You need to understand the upsides and downsides of each option and how they align with your company's needs. Of course, you can't base technical decisions on feelings. And there you were, watching them fight like football fans supporting their favorite team-MongoDB vs MySQL.
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