Home » Databases » MongoDB vs. The wide variety of database management systems DBMS on offer is undoubtedly a good thing. However, it also means that choosing the right database system for your needs requires more than just going with the most popular option.
From transaction model differences to the quality of support, DBMSs come in all shapes and sizes. However, unlike those systems, MongoDB is document-oriented. Another important feature of MongoDB is that it is schema-free.
It does not require defining a fixed structure during document creation and makes it significantly easier to change the record structure later. MongoDB Inc. These tables contain related data types that help structure data. MySQL stores related data in any number of separate tables. Querying and correlating data from those tables is facilitated by JOIN operations , which enable the creation of temporary tables and row sets using data from multiple tables. Oracle is the company that owns and offers support for MySQL.
At the time of writing this article, the latest stable release of MySQL is 5. Comparing them is useful because they are good representatives of their respective management philosophies. These documents have various structures, depending on the database requirements. The system stores related data together to facilitate quick querying. MongoDB does not need a table schema to be declared before allowing data input. A MongoDB document collection can feature documents with different sets of fields.
The field data type can also vary across documents. MySQL is an excellent choice if you have structured data and need a traditional relational database.
MongoDB is well-suited for real-time analytics, content management, the Internet of Things, mobile, and other types of applications. Delivery Hero. Accenture and more. It is a nimble database that allows fast changes of the cognitive framework when apps evolve. Artificial Intelligence AI and Machine Learning ML are transforming numerous areas of the economy and affecting parts of our regular lifestyles.
Industries like finance, health. Have you ever wished that you could build beautiful websites without going through the hassle of coding?
Not everyone has the best knowledge and experience. Thomas Wilfred October 10, Share This Post. Share on facebook. Share on linkedin. Share on twitter. Share on email. What is MongoDB? What big companies use MongoDB? Subscribe To Our Newsletter. Get updates and learn from the best. More To Explore.
Lucas White November 9, Lucas White November 6, Source: dev. Each MongoDB database contains collections, which in turn, are filled with documents. These documents can include various fields and types of information, allowing for data storage of documents that vary in content and size. In MySQL, since the data schema is more constrained, every row within a table requires the same columns, which can be particularly hard to manage when working with high-volume databases.
In other words, MongoDB document database is superior to MySQL relational database when dealing with diverse and large quantities of complex data. However, imagine a business working with fairly small and less diverse amounts of data: speed is not necessarily something to be concerned for since other features like reliability and data consistency have the priority. More important than comparing them in terms of speed, understanding the businesses' or projects' data requirements will determine which one is more suitable for your project and its potential to provide better results and performance.
MySQL is a mature and reasoned solution to ensure data privacy and integrity. Due to its explicit schema, MySQL creates reliable database structures by using tables that systematize data types, making the respective values queried adequately and easy to search. Since it requires data to be structured beforehand, this results in less technical debt.
Nonetheless, it can be a disadvantage in some cases, as it might be hard to design a suitable schema for complex data. Definitely, not an option for unstructured data. On the other hand, MongoDB has a more flexible and faster performance for unstructured data. Document datastores are good when the data schema is hard to design beforehand. However, if the data is diverse, then creating indexes on the data's attributes becomes challenging, which means MongoDB requires frequent optimization of the data schema.
Otherwise, it might be risking problems related to data consistency. MySQL utilizes a privilege-based security model , which requires user authentication and can also provide or deny user privileges on a particular database.
Plus, transferring data from the database to the server MySQL necessarily employs encrypted connections between clients and the server, using the Secure Sockets Layer SSL - a security protocol. MongoDB's security consists of role-based access control that includes authentication, authorization, and auditing. In computer science, ACID refers to a set of database transactions' properties that ensure data validity.
It stands for atomicity, consistency, isolation, and durability. If the indexes can reside entirely in memory, then 1 IO. So the total for mysql, even assuming that all indexes are in memory which is harder since there are 20 times more of them is about 20 range lookups.
These range lookups are likely comprised of random IO — different tables will definitely reside in different spots on disk, and it's possible that different rows in the same range in the same table for an entity might not be contiguous depending on how the entity has been updated, etc. Do you have concurrency, i. If you just run times the query straight, with just one thread, there will be almost no difference. Too easy for these engines :. Let me know when you get results, I'm also in need of inputs about this!
In short, the benefit comes from the design, not some raw speed difference. Conclusion on page The project tested, analysed and compared the performance and scalability of the two database types. The experiments done included running different numbers and types of queries, some more complex than others, in order to analyse how the databases scaled with increased load.
The most important factor in this case was the query type used as MongoDB could handle more complex queries faster due mainly to its simpler schema at the sacrifice of data duplication meaning that a NoSQL database may contain large amounts of data duplicates.
This advantage comes at the cost of data duplication which causes an increase in the database size. If such queries are typical in an application then it is important to consider NoSQL databases as alternatives while taking in account the cost in storage and memory size resulting from the larger database size. Stack Overflow for Teams — Collaborate and share knowledge with a private group.
Create a free Team What is Teams? Collectives on Stack Overflow. Learn more. Asked 9 years, 8 months ago. Active 1 year, 1 month ago. Viewed k times. Improve this question. Things like schemaless vs. How can it be faster in reading? It reads from a mechanical device. Same as MySQL. It depends on the speed of the device itself, you can't employ some weird magic via code in order to break trough the limits of hardware. ImranOmarBukhsh, indeedy. My perspective came from not recommending a change for change's sake - and suggesting a way that you can improve performance with your existing technology : — halfer.
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