MongoDB Atlas vs. Tanzu Data Services (Greenplum, GemFire, RabbitMQ, Tanzu SQL)

It is good if you: 1. Have unstructured data that you need to save (since it is NoSQL DB) 2. You don't have time or knowledge to setup the MongoDB Atlas, the managed service is the way to go (Atlas) 3. If you need a multi regional DB across the world

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If you need to execute ml algorithms, learning techniques, or mathematical calculations on large amounts of heterogeneous data, VMware Tanzu Data Services will be ideal. It will be really simple to set up, particularly if you choose AWS as your integrated cloud provider. However, if you're working with lower data amounts, such as gigabytes, it can be superfluous.

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• Generous free and trial plan for evaluation or test purposes.
• New versions of MongoDB are able to be deployed with Atlas as soon as they're released—deploying recent versions to other services can be difficult or risky.
• As the key supporters of the open source MongoDB project, the service runs in a highly optimized and performant manner, making it much easier than having to do the work internally.

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• Apache MADlib provides popular machine learning functionality.
• Allows you to query terabytes of data databases.
• Interoperability for AWS S3 is effortless.

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• For someone new, it could be challenging using MongoDB Atlas. Some official video tutorials could help a lot
• Pricing calculation is sometimes misleading and unpredictable, maybe better variables could be used to provide better insights about the cost
• Since it is a managed service, we have limited control over the instances and some issues we faced we couldn't;'t know about without reaching out to the support and got fixed from their end. So more control over the instance might help
• The way of managing users and access is somehow confusing. Maybe it could be placed somewhere easy to access

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• Running on Azure is a little more difficult.
• Synchronization with Kafka may be a little easier.

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I would give it 8. Good stuff: 1. Easy to use in terms of creating cluster, integrating with Databases, setting up backups and high availability instance, using the monitors they provide to check cluster status, managing users at company level, configure multiple replicas and cross region databases. Things hard to use: 1. roles and permissions at DB level. 2. Calculate expected costs

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We love MongoDB support and have great relationship with them. When we decided to go with MongoDB 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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They were very helpful. We needed support for initial implementation.

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MongoDB is a great product but on premise deployments can be slow. So we turned to Atlas. We also looked at Redis Labs and we use Redis as our side cache for app servers. But we love using MongoDB Atlas for cloud deployments, especially for prototyping because we can get started immediately. And the cost is low and easy to justify.

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• Positive - Faster provisioning so we don't have development teams waiting.
• Positive - Automated backups and server management - eliminates need for dedicated DBAs.

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• There was a noticeable reduction in system reliability.
• Saw a reduction in unsuccessful analytics operations.

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