MongoDB is an open source, cross-platform database management system (DBMS) that uses a document-oriented database model which supports various forms of data. It is one of the numerous non-relational database technologies which arose in the mid-2000s under the NoSQL banner for use in big data applications and other processing jobs involving data that doesn't fit well in a rigid relational model. Instead of using tables and rows as in relational databases, the MongoDB architecture is made up of collections and documents.
MongoDB is a document database. Instead of using tables’, rows as MySQL Database, MongoDB is based on the architecture of collections and documents. In MongoDB, the rows (or documents as called in MongoDB) do not need to have a schema defined beforehand. You can store any object without having to worry about the particular fields that compose this object and how to store them. The data model available within MongoDB allows you to represent hierarchical relationships, to store arrays, and other more complex structures more easily.
One of the advantages of using documents is that these objects map to native data types in a number of programming languages. Also, having embedded documents reduces the need for database joins, which can reduce costs.
MySQL database uses a structured query language (SQL) for defining and manipulating data. On one hand, this is extremely powerful: SQL is one of the most versatile and widely-used options available, making it a safe choice and especially great for complex queries. On the other hand, it can be restrictive. SQL requires that you use predefined schemas to determine the structure of your data before you work with it.
When comparing the speed to MongoDB to that of MySQL, it is noted by developers that MySQL lacks speed and experiences difficulties with large data volume compared to MongoDB. As the number of queries increases SQL takes more time to execute those queries but the performance of MongoDB is better in such a scenario. MongoDB possesses some routine factors that are responsible for its high performance; embedding documents, it avoids the concept of joins and provides indexing of data. MySQL is a better choice for companies with smaller databases looking for a general solution.
Unlike MongoDB, MySQL supports Atomic Transaction. ACID compliance (Atomicity, Consistency, Isolation, and Durability) reduce anomalies and protects the integrity of your database by prescribing exactly how transactions interact with the database. Generally, NoSQL databases sacrifice ACID compliance for flexibility and processing speed. MongoDB is not the best option for applications with complex transactions.
MongoDB uses dynamic schemas that eliminate the need to pre-define the structure, like fields or value types. Such a model allows hierarchical relationships representation, array storage, and ability to change the records structure by simply adding or deleting fields. This NoSQL solution comes with embedding, auto-sharding, and on-board replication for better scalability and high availability. This is one of the major benefits offered by MongoDB.
MySQL databases are vertically scalable, meaning a single server must be made increasingly powerful in order to deal with increased demand. It is possible to spread the SQL database over many servers, but significant additional engineering is generally required, and core relational features such as Joins, referential integrity and transactions are typically lost. MongoDB, on the other hand, are horizontally scalable, meaning that to add capacity, a database administrator can simply add more commodity servers or cloud instances. The database automatically spreads data across servers as necessary. It helps reduce the workload and scale your database with ease.
In conclusion, MySQL is a strong choice for any business that will benefit from its pre-defined structure and set schemas. MongoDB, on the other hand, is a good choice for businesses that have rapid growth or databases with no clear schema definitions.
Programming Languages and Resources for Web Developers
SQL or MongoDB coding is well suited for those interested in pursuing a career in web design and development; however, other options are mobile App design and development, system admin and software engineering. It is advisable to consult with an IT career counselor to understand what career options best fits your skills. For instance, if you want to be a software engineer, learning HTML and CSS might not fit the bill. Here is an excellent article for learning more on coding and technology career roadmap. Once you know what career path you wish to pursue, you can make a plan on what, when, and how to learn. There are lots of online resources for learning coding and technology in general. For teenagers and high school students, High School Technology Services offers variety of hands-on training. For adults and professionals, Coding Bootcamps and DC Web Makers Companies offer basic to advance project-based programming and technology classes.