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.
I have used them sometimes, even recently, and found the feedback to be spot on our needs.
The features of MongoDB Atlas fall short, resulting in an average rating due to higher-expectation features still lacking in its offerings.
For premium support, I would rate the support of MongoDB Atlas a nine.
I received great support in migrating data to Snowflake, with quick responses and innovative solutions.
I am satisfied with the work of technical support from Snowflake; they are responsive and helpful.
The technical support from Snowflake is very good, nice, and efficient.
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.
Snowflake is very scalable and has a dedicated team constantly improving the product.
The billing doubles with size increase, but processing does not necessarily speed up accordingly.
Recently, Snowflake has introduced streaming capabilities, real-time and dynamic tables, along with various connectors.
When it comes to OLTP transactions, its performance declines.
The stability of the product is very high.
Snowflake is very stable, especially when used with AWS.
Snowflake as a SaaS offering means that maintenance isn't an issue for me.
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.
Enhancements in user experience for data observability and quality checks would be beneficial, as these tasks currently require SQL coding, which might be challenging for some users.
What things you are going with to ask the support and how we manage the relationship matters a lot.
If more connectors were brought in and more visibility features were added, particularly around cost tracking in the FinOps area, it would be beneficial.
For our service, it was around 300 to 600 euros per month, which was acceptable for our customers.
The price of MongoDB Atlas is reasonable, which is why many organizations, including mine, are opting for it.
Snowflake's pricing is on the higher side.
Snowflake lacks transparency in estimating resource usage.
I find MongoDB Atlas highly scalable and easy to use, with very good support.
It is particularly useful for unstructured and semi-structured data because of its performance in these areas.
The most valuable features of MongoDB Atlas in handling large data volumes include collection size and its NoSQL database capabilities.
We had a comparison with Databricks and Snowflake a few months back, and this auto-scaling takes an edge within Snowflake; that's what our observation reflects.
I have used the Snowflake Zero-Copy Cloning feature in the past while prototyping data in lower environments. This feature is helpful as it saves a lot of time during the data replication process.
Snowflake is a data lake on the cloud where all processing happens in memory, resulting in very fast query responses.
| Product | Market Share (%) |
|---|---|
| Snowflake | 5.7% |
| MongoDB Atlas | 2.1% |
| Other | 92.2% |
| Company Size | Count |
|---|---|
| Small Business | 23 |
| Midsize Enterprise | 10 |
| Large Enterprise | 20 |
| Company Size | Count |
|---|---|
| Small Business | 29 |
| Midsize Enterprise | 20 |
| Large Enterprise | 58 |
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.
Snowflake provides a modern data warehousing solution with features designed for seamless integration, scalability, and consumption-based pricing. It handles large datasets efficiently, making it a market leader for businesses migrating to the cloud.
Snowflake offers a flexible architecture that separates storage and compute resources, supporting efficient ETL jobs. Known for scalability and ease of use, it features built-in time zone conversion and robust data sharing capabilities. Its enhanced security, performance, and ability to handle semi-structured data are notable. Users suggest improvements in UI, pricing, on-premises integration, and data science functions, while calling for better transaction performance and machine learning capabilities. Users benefit from effective SQL querying, real-time analytics, and sharing options, supporting comprehensive data analysis with tools like Tableau and Power BI.
What are Snowflake's Key Features?
What Benefits Should You Look for?
In industries like finance, healthcare, and retail, Snowflake's flexible data warehousing and analytics capabilities facilitate cloud migration, streamline data storage, and allow organizations to consolidate data from multiple sources for advanced insights and AI-driven strategies. Its integration with analytics tools supports comprehensive data analysis and reporting tasks.
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