You might be familiar with the relational database management system that is being used to manage a structured database with the help of tables, rows, and columns. Relied queries are being used to store and access organized data from these databases. While SQL is considered as one of the best ways to manage structured databases, it is not capable of handling the unstructured data. It is not a flexible or reliable solution to process the unstructured data produced by organizations these days regularly.
To manage the unstructured data like videos, audios, chat logs, images, and IoT data, NoSQL databases are considered as one of the best solutions. NoSQL databases can store unstructured data in an organized manner, and DynamoDB and MongoDB are two top choices here.
Each has its own benefits and drawbacks. Now how to decide the better choice among both? Through this blog we would help you explore both popular NoSQL databases.
Proprietary NoSQL database service of Amazon, named as DynamoDB and it is offered as the part of Amazon Web Service portfolio. It is known for its fast and predictable performance. Few of the Amazon’s teams have adopted it due to its high operational complexity and the best performance, reliability, data consistency, and query flexibility.
With the help of DynamoDB, user can create tables that can store any type of data and can handle any type of service request. Moreover, as per the requirement, you can scale up and scale down the table size without impacting the database performance in any way. You can use the AWS management console to provide top performance and best resource utilization features.
With the help of these features, MongoDB can easily handle and store unstructured data and is considered as one of the most reliable NoSQL databases available so far. Now as we have discussed the basics of MongoDB and DynamoDB, it is the right time to compare or differentiate these databases based on various parameters.
Many of the terminologies of these databases are quite similar. Below table has some of the commonly used terms in both of these databases.
|Secondary Index||Secondary Index|
DynamoDB is a proprietary database available only with Amazon Web Services. One can also download a version of DynamoDB that is available for prototyping any local machine. The DynamoDB can run on an AWS production. For DynamoDB, one can directly go to the AWS console to create a database.
As far as MongoDB setup and deployment is concerned, it is quite difficult to set up the MongoDB environment. For that, the user has to just enter the terminal text and may have to face unexpected errors. Sometimes, these errors can be fixed just in a few minutes and sometime it may take longer to fix similar errors.
If you are fluent in using Ubuntu terminal, then it may be quite easier for you to install and set up the MongoDB. You can also use the paid subscription of “MongoDB Atlas support” that is a cloud-hosted version. Though there are some documents available on the MongoDB site, they are not enough to fix the installation errors for MongoDB. These documents are suitable for Ubuntu terminals, so if you are using any other terminal, then you may have to face the installation challenges. MongoDB Atlas, a cloud-based version of the database is easy to install and use rather than using MongoDB.
MongoDB uses JSON like documents to store unstructured data. A collection of documents that do not require any pre-defined structure and columns can be used in MongoDB that may be different for every document as well.
It has lots of similar features as of relational databases like expressive query language, strong consistency, etc. As it is a schema-free structure, so you can create a document without creating any structure for the document. A comparison between RDBMS and MongoDB is given below:
Here, it signifies that collections in MongoDB are like tables of RDBMS and Documents are like Records.
Indexes help you to access the alternate query patterns and speed up the queries. In DynamoDB, you can create the secondary indexes, just like the RDBMS. You can create the secondary indexes by specifying the key attributes and create a query for the same. DynamoDB does not have query optimizer, so the secondary indexes are only used just to execute query and scanning purposes.
In MongoDB, indexes are mostly preferred to store the database. In case, if any single index is missing, the entire document is searched to select the data through a query. It can slow down the read time of any query.
For DynamoDB, you may require to do some efforts and put more time to design database tables, indexes, keys, attributes, etc. that may be required and essential for effective query designing. While MongoDB users can use and access a flexible APU to design query attributes that may include deep and nested indexing that is closer to the relational database.
As far as database scaling is concerned, then one of the major advantages of Amazon DynamoDB is that it can be easily scaled to petabytes and can handle a huge throughput just with the help of a simple configuration. DynamoDB uses internal clustering, so it offers the best and improved performance to database developers.
DynamoDB can be auto-scaled with minimal configuration without being worried about the underlying infrastructure. While MongoDB provides somewhat similar solutions and features, you can also deploy your own MongoDB clusters within AWS. These MongoDB clusters can be scaled out as well to provide better performance. But you may not get Amazon support and high throughput like DynamoDB.
You can compare it as per the nature of workload towards database systems. Like if your queries contain a listing of multiple items, then Amazon DynamoDB may be expensive for you. Amazon charges mostly for the performance improvement from its clients. If the frequency of queries is high, then users have to pay a high amount to Amazon.
For MongoDB that cost is paid for infrastructure or as per the availability and external backups to manage the services. The throughput is also included under its pricing. For small applications for which the throughput requirement is low, AWS DynamoDB may be less inexpensive. This cost may be operational and management cost.
Amazon DynamoDB is a completely managed NoSQL database. You may have to put minimum efforts to manage Amazon’s DynamoDB. In DynamoDB, you can create the tables just by executing a single line of code. DynamoDB can also use internal functionalities for backup and restore and encryption. Moreover, there is no entity like database in DynamoDB that can eliminate the database functionalities like managing its operating system and software update, etc. MongoDB also comes with fully managed solutions like MLab. You can also use this simple to manage functionality to manage the clusters of MongoDB or can put them in AWS Datacenter to manage them. Still, you will have to manage certain other things like deployment setup or to set up a VPN connection. If you are going to manage your MongoDB cluster inside AWS Datacenter, then you will have to take care of certain things like setting up Networks, Security and Backups, Clustering, etc. that may be challenging for you. Well, users can also use third-party solutions to manage MongoDB backup.
DynamoDB was launched in September 2013 by Amazon, and it made the database available for public use so that that database developer can test DynamoDB applications on their own. It is a part of Amazon Web Services.
MongoDB was started in 2007 by 10gen, that created the product-based word. It was released in 2009; later the company name changed to MongoDB Inc that provides development of software and handles its enterprise solution.
If you are already using AWS stack for other operations and need a NoSQL database to manage the information, then DynamoDB is a must-have choice for you. For IoT and gaming industry too, DynamoDB is again a popular choice. But you will not be able to use embedded data structures here like MongoDB. If you need scalability and caching like real-time features, then MongoDB can be the option for you. Though, it is not mended for transactional data, it is usually used for content management, mobile apps, and real-time applications. It is clear that both databases have their own benefits and drawbacks, so you need to analyze the project requirements first and decide on the best database system accordingly.
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