MongoBD is a fairly young but promising DRR. It combines the qualities of simple databases that do not use SQL queries (NoSQL-DBMS) and powerful databases with the maximum set of functions. It is reported that MongoBD should become a bridge between the two main types of databases. MongoBD is used by MTV, CNN, New York Times, and other well-known companies and institutions. The MongoBD language is the most popular C++ language. Type - an open source, document-based DBMS that is not a relational database. One of the most useful qualities is automatic segmentation of documents by replicas. The segment key is used for this purpose.
Among the advantages we can also note the less demanding attitude to computational resources due to the minimalization of the system semantics. This also simplifies horizontal scaling. It increases performance, makes it easier to manage the base. Naturally, there are also disadvantages, especially given the young age of the base. If a size limit is set and you want to update a document that is larger than the previous version, it will simply not be updated. The system uses large volumes on the hard disk drive - the largest number of DRRs. To work with data whose size is more than 4 GB you need 64-bit servers. Updating is carried out in such a way that if the process is interrupted for any reason, some documents will not be updated. However, MongoBD appears to be a very promising program aimed at the future. The system is constantly updated, minor errors and bugs are fixed. This DBMS will be interesting for those who need a compromise between the power of SQL-bases and the speed of the simplest systems.
One main benefit of using MongoDB is its ability to seamlessly handle large volumes of data while maintaining speed and performance.
- the size of the collection may be forcibly limited to a specific size, and if that size is exceeded, the old information will be deleted;
- Journaling and two types of asynchronous replications are supported;
- Automatic segmentation of documents by range;
- Full support for full-text search in many languages, including Russian.