MongoDB Atlas is generally considered to be ahead of Microsoft, though behind Amazon as a cloud-based non-relational database, in terms of functionality. Users score it well on ease of use.
It is particularly strong among developers, small businesses, and in companies with an open source heritage. The only major drawback is its anomaly detection; even smaller firms that want to perform anomaly detection will see the lack here.
In terms of market share, it is far behind Oracle, Microsoft and Amazon. Thus, it is likely to only be an option in firms with familiarity with open source tools. However, it is gaining traction via a free Atlas tier offered in AWS, Google Cloud Platform and Microsoft Azure. As it uses non-relational NoSQL, it may be problematic for some complex queries. Those unfamiliar with MongoDB are advised to try out the free version before adding it to shortlists.
MongoDB Atlas is a fully managed, global cloud database that runs on Amazon Web Services, Microsoft Azure, and Google Cloud Platform. Operational and security practices are built in. Automation of infrastructure provisioning, database setup, and backup aid ease of use. Global Clusters allow users to create policies to position data for distributed applications. Policy enables data to be distributed and isolated within certain geographic boundaries. Data can also be moved closer to end users for low-latency performance.
Additionally, MongoDB Charts allow users to create data visualizations and share them without having any code to write, tools to configure, data movement or duplication. MongoDB Charts natively support the document model in order to remove the complexity of visualizing hierarchical JSON data. Users do not require any engineering knowledge into how the data was structured to build visualizations.
Users can create a free account and spin up free MongoDB Atlas databases with no credit card required. A credit card is needed to spin up a dedicated Atlas database cluster.
Non-relational, document databases.
Hundreds of thousands of operations per second
“It is very easy to use and we have been able to scale from to terabytes easily. The integration and configuration of MongoDB in the AWS environment is quite good,” said an Engineer at a utility. “But moving data from other databases into MongoDB, along with indexing, was challenging.”
Automated sharding for scale out, and zero-downtime scale up to larger instance types. No practical limit in terms of data size due to horizontal scaling. Users can provision TBs of database storage on SSDs with dedicated I/O bandwidth.
Security features include TLS/SSL encryption, authentication, and authorization via SCRAM; network isolation and VPC Peering on AWS; IP whitelists; encrypted storage volumes; and the MongoDB Atlas console to manage database users.
Atlas comes with a fully managed backup service with continuous, consistent backups and point-in-time recovery, backed by retention policies.
- Global businesses facing regional data compliance challenges (e.g. GDPR)
- High-growth startups
- Fortune 2000 companies modernizing their technology infrastructure
“The UI can be difficult to understand,” said a Technical Director for an innovation lab.
Pricing is tiered based on instance size. As an example, a 3-instance set with each instance having 16 GB RAM, 80 GB storage, 240 IOPS would cost $0.77/ hr or ~$560/mo. Users can start for free with 512 MB storage. They can get more storage (2 GB) starting at $9/month.
|Performance||100k+ ops per sec|
|Core Markets||Global businesses with compliance challenges
|Pricing||3-instance set with each instance having 16 GB RAM, 80 GB storage, 240 IOPS would cost $0.77/ hr|
|Key Differentiator||Strong focus on open source|