Likelihood to Recommend
It is suitable for database administrative operations that require a high level of speed, since by not working with conventional SQL it is possible to create data records faster, and therefore better manage work time. It is not necessary to create backend connections for the databases, since these backends of different web pages and applications automatically centralize the development data in a single place, which is useful when managing many services in parallel. It is much easier and faster to get a specific document based on special characteristics of your data, through the filtering system of MongoDB Atlas, since it manages large numbers of servers, and has a high capacity of data mimicry. The cluster shows a history of all the operations that have been performed during the day, so that it is easy to make job regressions in case you need to identify an error that occurred at some point during the day. All data from the MongoDB web application is automatically stored in the Atlas cloud.
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Production ready, robust DB solution built for
envs, we was able, for the first time, to ship production db workloads inside k8s. Be sure to check differences with "traditional"
and other clustering solutions. Also be sure to match it with proper k8s storage solutions.
Read full review Pros No infrastructure on our side. Free of management. Easy to scale up and down. Read full review Easy and fast deployment. A reliable, fully automated, high-available db lifecycle management solution. Exaustive documentation. Production ready. Read full review Cons Read full review Some differences compared to "traditional" MySQL solution. Had some hard times trying to use it combined with pre-existing techs like WordPress, Magento, etc. The specific k8s environment features can have an impact on it, like the storage solutions offered by the cloud vendor. Read full review Usability
Easy and fast deployment. A reliable, fully automated, high-available db lifecycle management solution. It requires a bit of learning time for people new to operators ecosystem.
Read full review Support Rating
support and have great relationship with them. When we decided to go with
Atlas, they sent a team of 5 to our company to discuss the process of setting up a Mongo cluster and walked us through. when we have questions, we create a ticket and they will respond very quickly
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Well documented, there was no need to contact support.
Read full review Alternatives Considered
When choosing a NoSQL, open source database, MongoDB is the clear winner from an implementation standpoint. For databases that are better suited for highly-organized data, a traditional database engine like
, or Oracle's RDBMS may be a better choice. When the requirement is for a NoSQL production database, MongoDB and Atlas are the clear winners from an implementation and management perspective and is very cost-competitive with offerings from Azure Cosmos and Amazon Document DB.
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For a long time we struggled finding a viable solution to migrate our existing db workloads inside
. Before "operators era" proper db workloads required manual management, of course that easily raised administrative overhead. Then the future started to be brighter with the introduction of operators and the "official" Oracle's
Operator, then Presslab's one, finally Percona's operator. Compared to other operators, the last one allowed us to ship production db workloads inside k8s.
Read full review Return on Investment Since we can cover a much more exhaustive database management with MongoDB Atlas, we can say that we have partly increased our profit intake in relation to the time we have been using the software. MongoDB Atlas has improved our earnings by 400%, which leaves our current ROI at a percentage of 5, having achieved our first 200% in the first half year of using the software. Read full review It allowed us to use k8s on our entire infrastructure. Decreased administrative overhead around our db services. As it is an open source technology, it cut down our db pricings. Read full review