> For the complete documentation index, see [llms.txt](https://functional.gitbook.io/database_comparison_report/llms.txt). Markdown versions of documentation pages are available by appending `.md` to page URLs; this page is available as [Markdown](https://functional.gitbook.io/database_comparison_report/mongo-db/cons-of-mongo-db.md).

# Cons of Mongo DB

**Extensive memory consumption.** The denormalization process, when previously normalized data in a database is grouped to increase performance, usually results in high memory consumption. Also, this DBMS keeps in memory all key names for each value pair. Beyond that, because there is no support for joins, Mongo databases have data oversupply, resulting in big memory waste and lower application performance.

**Data insecurity.** With a focus on fast data operation, MongoDB, like any other NoSQL DBMS, lacks data security. As user authentication isn’t a default Mongo option, and higher protection is available with a commercial edition only, you can’t consider it totally secure. Additionally, there are constant MongoDB update releases, with no guarantee that all amendments or data changes will work as they did before. Keep in mind that all manipulations should be formed around these updates, being covered with additional tests.

**Complicated process to interpret into other query languages.** As MongoDB wasn’t initially developed to deal with relational data models, the performance may slow down in these cases. Besides, the translation of SQL to MongoDB queries takes additional action to use the engine, which may delay the development and deployment.