Find out in this report how the two Database Management Systems (DBMS) solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
I find it easy to use.
Whenever we need support, if there is an issue accessing stored data due to regional data center problems, the Amazon team is very helpful and provides optimal solutions quickly.
It's costly when you enable support.
The features of MongoDB Atlas fall short, resulting in an average rating due to higher-expectation features still lacking in its offerings.
I have used them sometimes, even recently, and found the feedback to be spot on our needs.
For premium support, I would rate the support of MongoDB Atlas a nine.
The scalability part needs improvement as the sizing requires trial and error.
It's very much scalable, and I would rate scalability a nine.
MongoDB Atlas offers sharding as a scalability feature, although it does not perform as well as Oracle.
Amazon Redshift is a stable product, and I would rate it nine or ten out of ten for stability.
When it comes to OLTP transactions, its performance declines.
The stability of the product is very high.
They should bring the entire ETL data management process into Amazon Redshift.
Integration with AI could be a good improvement.
Enhancing capabilities for data pipelines and visualization dashboards.
MongoDB Atlas should support containerization.
I would say pricing is an area where MongoDB Atlas could improve.
The cost of technical support is high.
It's a pretty good price and reasonable for the product quality.
The pricing of Amazon Redshift is expensive.
The price of MongoDB Atlas is reasonable, which is why many organizations, including mine, are opting for it.
For our service, it was around 300 to 600 euros per month, which was acceptable for our customers.
Amazon Redshift's performance optimization and scalability are quite helpful, providing functionalities such as scaling up and down.
Scalability is the best feature of Amazon Redshift. Amazon Redshift handles scalability automatically, so we do not need to scale up or down; it is all managed by Redshift.
Scalability is also a strong point; I can scale it however I want without any limitations.
The most valuable features of MongoDB Atlas in handling large data volumes include collection size and its NoSQL database capabilities.
I find MongoDB Atlas highly scalable and easy to use, with very good support.
MongoDB Atlas's encryption capabilities help ensure data confidentiality and integrity.
| Product | Market Share (%) |
|---|---|
| MongoDB Atlas | 2.1% |
| Amazon Redshift | 4.4% |
| Other | 93.5% |
| Company Size | Count |
|---|---|
| Small Business | 27 |
| Midsize Enterprise | 21 |
| Large Enterprise | 28 |
| Company Size | Count |
|---|---|
| Small Business | 23 |
| Midsize Enterprise | 10 |
| Large Enterprise | 20 |
Amazon Redshift is a fully administered, petabyte-scale cloud-based data warehouse service. Users are able to begin with a minimal amount of gigabytes of data and can easily scale up to a petabyte or more as needed. This will enable them to utilize their own data to develop new intuitions on how to improve business processes and client relations.
Initially, users start to develop a data warehouse by initiating what is called an Amazon Redshift cluster or a set of nodes. Once the cluster has been provisioned, users can seamlessly upload data sets, and then begin to perform data analysis queries. Amazon Redshift delivers super-fast query performance, regardless of size, utilizing the exact SQL-based tools and BI applications that most users are already working with today.
The Amazon Redshift service performs all of the work of setting up, operating, and scaling a data warehouse. These tasks include provisioning capacity, monitoring and backing up the cluster, and applying patches and upgrades to the Amazon Redshift engine.
Amazon Redshift Functionalities
Amazon Redshift has many valuable key functionalities. Some of its most useful functionalities include:
Reviews from Real Users
“Redshift's versioning and data security are the two most critical features. When migrating into the cloud, it's vital to secure the data. The encryption and security are there.” - Kundan A., Senior Consultant at Dynamic Elements AS
“With the cloud version whenever you want to deploy, you can scale up, and down, and it has a data warehousing capability. Redshift has many features. They have enriched and elaborate documentation that is helpful.”- Aishwarya K., Solution Architect at Capgemini
MongoDB Atlas stands out with its schemaless architecture, scalability, and user-friendly design. It simplifies data management with automatic scaling and seamless integration, providing dynamic solutions for diverse industries.
MongoDB Atlas offers a cloud-based platform valued for its seamless integration capabilities and high-performance data visualization. It features advanced security options such as encryption and role-based access control alongside flexible data storage and efficient indexing. Users benefit from its robust API support and the ability to manage the platform without an extensive setup process. Feedback suggests improvements are needed in usability, query performance, security options, and third-party tool compatibility. While pricing and support services could be more economical, there is a demand for enhanced real-time monitoring and comprehensive dashboards, as well as advanced containerization and scalability options supporting complex database structures.
What are the key features of MongoDB Atlas?
What benefits should you consider in a solution like MongoDB Atlas?
In healthcare and finance, MongoDB Atlas manages payment transactions and facilitates real-time analytics, powering SaaS solutions and storing large volumes of user data. It enhances scalability, performance, and security for cloud hosting, IoT integrations, and Node.js environments, widely favored for its flexibility and capability to support microservices.
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