Comparison between DynamoDB and MongoDB
All the databases that are required by any big or small company for their content system, expect a highly customized one, which allows storing thousands and thousands of storage capacity. Hence database of each type include set of fields which factually lend by own efficiently to a traditional RDBMS system say for Oracle, or MySQL et al.
When there is a requirement for storing huge data, the most common relational database does not suit fit but of in wide use. Making use of standard rules, individual tables could create to hold all the entities of the data, however; technical minds seek for the better one. Hence, DynamoDB appears when MongoDB is in existence.
That MongoDB is an open source and document-oriented database. However, it is designed with developer agility and scalability features, it stores data/information in a relational database structure instead of rows and columns. It allows you to store JSON data models mapped with relevant applications with dynamic schemas. It leaves the storage process simple and efficient that the developer can iterate rapidly in which inbuilt drivers for the languages of respective codes.
With no extra coding required, MongoDB has an expressive query language that allows the developers to set, align and cumulate the data efficiently. It works on an auto-managing capability that requires no downtime and with one single click for data storing processes.
It gets affordable along with budget too, however, executing in the cloud on the commodity hardware within the data center hence managing the failovers on the own. All right! Then why DynamoDB over leads it, of course, DynamoDB has features that are most grateful to the developer's side, however, it seems to compare cereals and pulses!
Amazon DynamoDB provides a rapid and predictable performance with its fully managed NoSQL database service. With its seamless tenacity, it lets the developers offload the administrative burdens such as executing and scaling the distributed database hence hassle-free hardware provisioning, setup, configuration, replication, and software patching or cluster scaling could take place.
Database tables of any amount of data can be stored and retrieved with DynamoDB at any level of traffic space. In addition, it allows scaling up and down the tables with firm temperament and with no downtime in terms of performance degradation. AWS management helps in handy along with DynamoDB to monitor the resource usage and performance metrics.
Appending below are the salient features of DynamoDB that are very compelling making the developers get attention towards it when comparing to MongoDB:
DynamoDB executes analyzing unstructured data in terms of easy elastic map reduce integration hence no hassles for the developers wherein MongoDB has set limits when executing map reduce processes. Almost most of the NoSQL databases systems have not factually met the expectation level as like DynamoDB so far. In fact, extending the analytics application for a database structure is a bit complex job, wherein it requires database request for the result to be sent back.
DynamoDB supports on auto management that it never relies on hardcore replication of the values. Similar to the Amazon products’ offerings, the reading and writing units could be adjusted very easily on its factual process.
3. Easy kick-start
All the developer needs to have one AWS account to kick start the hosting solution wherein DynamoDB allows the execution as easy as making an API calls. Unlike other NoSQL systems, it does not require exact server allocation, installation and configuration prompt. DynamoDB needs to have a focused application and leaves the rest to AWS to handle everything.
DynamoDB takes single digit latency for heavy-load database management process in which all the information was replicated synchronously across all the available zones. However, it does not require downtime throughout the process.