Amazon Web Services (AWS) is a subsidiary of Amazon that provides on-demand cloud computing services. With over 165 services offered, AWS services can provide users with a comprehensive suite of infrastructure and computing building blocks and tools.
$100
per month
MongoDB
Score 8.9 out of 10
N/A
MongoDB is an open source document-oriented database system. It is part of the NoSQL family of database systems. Instead of storing data in tables as is done in a "classical" relational database, MongoDB stores structured data as JSON-like documents with dynamic schemas (MongoDB calls the format BSON), making the integration of data in certain types of applications easier and faster.
$0.10
million reads
Pricing
Amazon Web Services
MongoDB
Editions & Modules
Free Tier
$0
per month
Basic Environment
$100 - $200
per month
Intermediate Environment
$250 - $600
per month
Advanced Environment
$600-$2500
per month
Shared
$0
per month
Serverless
$0.10million reads
million reads
Dedicated
$57
per month
Offerings
Pricing Offerings
Amazon Web Services
MongoDB
Free Trial
Yes
Yes
Free/Freemium Version
Yes
Yes
Premium Consulting/Integration Services
No
No
Entry-level Setup Fee
No setup fee
No setup fee
Additional Details
AWS allows a “save when you commit” option that offers lower prices when you sign up for a 1- or 3- year term that includes an AWS service or category of services.
Fully managed, global cloud database on AWS, Azure, and GCP
Rackspace loses to AWS on both features and price, and their reputation for top-notch customer service just doesn't make up for it, especially if you have talented ops resources who find themselves rarely dependent upon support channels. Even when they do, AWS has a very active …
MySQL is a great for querying related data, but it's unable to store structured data and has a fixed schema. Also SQL can be non-intuitive. DynamoDB, CouchDB and Redis all make querying the data quite difficult and lack important features. The problem CouchDB tries to solve is …
Features
Amazon Web Services
MongoDB
Infrastructure-as-a-Service (IaaS)
Comparison of Infrastructure-as-a-Service (IaaS) features of Product A and Product B
Amazon Web Services
8.4
78 Ratings
2% above category average
MongoDB
-
Ratings
Service-level Agreement (SLA) uptime
9.072 Ratings
00 Ratings
Dynamic scaling
8.873 Ratings
00 Ratings
Elastic load balancing
9.369 Ratings
00 Ratings
Pre-configured templates
7.166 Ratings
00 Ratings
Monitoring tools
8.473 Ratings
00 Ratings
Pre-defined machine images
8.366 Ratings
00 Ratings
Operating system support
7.972 Ratings
00 Ratings
Security controls
8.674 Ratings
00 Ratings
Automation
8.325 Ratings
00 Ratings
NoSQL Databases
Comparison of NoSQL Databases features of Product A and Product B
This is something that is actually common across most cloud providers. A comprehensive understanding of one's use cases, constraints and future directions is key to determining if you even need a cloud solution. If you are a 2-person startup developing something with a best-scenario audience of 1k DAU in a year, you would very likely best served by a dirt-cheap dedicated Linux server somewhere (and your options to graduate to a cloud solution will still be open). If, however, you are a bigger fish, and/or you are actively considering build-vs-buy decisions for complicated, highly-loaded, six-figure requests per minute systems, global loadbalancing, extreme growth projections - then MAYBE you solve all or part of it with a cloud provider. And depending on your taste for risk, reliability, flexibility, track record - it might be AWS.
If asked by a colleague I would highly recommend MongoDB. MongoDB provides incredible flexibility and is quick and easy to set up. It also provides extensive documentation which is very useful for someone new to the tool. Though I've used it for years and still referenced the docs often. From my experience and the use cases I've worked on, I'd suggest using it anywhere that needs a fast, efficient storage space for non-relational data. If a relational database is needed then another tool would be more apt.
Being a JSON language optimizes the response time of a query, you can directly build a query logic from the same service
You can install a local, database-based environment rather than the non-relational real-time bases such a firebase does not allow, the local environment is paramount since you can work without relying on the internet.
Forming collections in Mango is relatively simple, you do not need to know of query to work with it, since it has a simple graphic environment that allows you to manage databases for those who are not experts in console management.
An aggregate pipeline can be a bit overwhelming as a newcomer.
There's still no real concept of joins with references/foreign keys, although the aggregate framework has a feature that is close.
Database management/dev ops can still be time-consuming if rolling your own deployments. (Thankfully there are plenty of providers like Compose or even MongoDB's own Atlas that helps take care of the nitty-gritty.
We are almost entirely satisfied with the service. In order to move off it, we'd have to build for ourselves many of the services that AWS provides and the cost would be prohibitive. Although there are cost savings and security benefits to returning to the colo facility, we could never afford to do it, and we'd hate to give up the innovation and constant cycle of new features that AWS gives us.
I am looking forward to increasing our SaaS subscriptions such that I get to experience global replica sets, working in reads from secondaries, and what not. Can't wait to be able to exploit some of the power that the "Big Boys" use MongoDB for.
AWS offers a wide range of powerful services that cater to various business needs which is significant strength. The ability to scale resources on-demand is a major advantage making it suitable for businesses of all sizes. The sheer volume of options and configurations can be overwhelming for new users leading to a steep learning curve. While functional the AWS management console can feel cluttered and less intuitive compared to some competitors which can hinder navigation. Although some documentation lacks clarity and practical examples which can frustrate users trying to implement specific solutions.
NoSQL database systems such as MongoDB lack graphical interfaces by default and therefore to improve usability it is necessary to install third-party applications to see more visually the schemas and stored documents. In addition, these tools also allow us to visualize the commands to be executed for each operation.
AWS does not provide the raw performance that you can get by building your own custom infrastructure. However, it is often the case that the benefits of specialized, high-performance hardware do not necessarily outweigh the significant extra cost and risk. Performance as perceived by the user is very different from raw throughput.
The customer support of Amazon Web Services are quick in their responses. I appreciate its entire team, which works amazingly, and provides professional support. AWS is a great tool, indeed, to provide customers a suitable way to immediately search for their compatible software's and also to guide them in a good direction. Moreover, this product is a good suggestion for every type of company because of its affordability and ease of use.
Finding support from local companies can be difficult. There were times when the local company could not find a solution and we reached a solution by getting support globally. If a good local company is found, it will overcome all your problems with its global support.
While the setup and configuration of MongoDB is pretty straight forward, having a vendor that performs automatic backups and scales the cluster automatically is very convenient. If you do not have a system administrator or DBA familiar with MongoDB on hand, it's a very good idea to use a 3rd party vendor that specializes in MongoDB hosting. The value is very well worth it over hosting it yourself since the cost is often reasonable among providers.
Amazon Web Services fits best for all levels of organisations like startup, mid level or enterprise. The services are easy to use and doesn't require a high level of understanding as you can learn via blogs or youtube videos. AWS is Reasonable in cost as the plan is pay as you use.
We have [measured] the speed in reading/write operations in high load and finally select the winner = MongoDBWe have [not] too much data but in case there will be 10 [times] more we need Cassandra. Cassandra's storage engine provides constant-time writes no matter how big your data set grows. For analytics, MongoDB provides a custom map/reduce implementation; Cassandra provides native Hadoop support.
Using Amazon Web Services has allowed us to develop and deploy new SAAS solutions quicker than we did when we used traditional web hosting. This has allowed us to grow our service offerings to clients and also add more value to our existing services.
Having AWS deployed has also allowed our development team to focus on delivering high-quality software without worrying about whether our servers will be able to handle the demand. Since AWS allows you to adjust your server needs based on demand, we can easily assign a faster server instance to ease and improve service without the client even knowing what we did.
Open Source w/ reasonable support costs have a direct, positive impact on the ROI (we moved away from large, monolithic, locked in licensing models)
You do have to balance the necessary level of HA & DR with the number of servers required to scale up and scale out. Servers cost money - so DR & HR doesn't come for free (even though it's built into the architecture of MongoDB