Coremetrics / IBM Digital Analytics (discontinued) vs. MongoDB Atlas

IBM analytics has continued to improve upon the days of being the original core metrics. After using the updated version for quite some time, it has been great at providing the needed analytics to measure ROI and goal performance for our quarterly KPI's. It has resulted in a great increase in web engagements although we are a midsize company, smaller outfits may not need such an expensive option.

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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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• IBM CXA comprises an acquisition called Tealeaf. This tool has deep heritage and this is evident in its present-day capabilities.
• The Universal Behaviour Exchange or UBX puts the concept of personalisation at the forefront. The ability to combine physical (analog) and digital transactions to create the complete picture of a customer journey, is a stand out benefit.
• The solution does not have to involve the purchase of software. IBM CXA can be sold as a service bundled with analytics as a service. This not only lowers the cost of ownership, it gets around one of the principal issues. Strong staff with design and analytical capability to drive the solution and deliver tangible benefits.
• The seamless integration of Watson AI services to help with the heavy lifiting. Watson reinforces the analytical focus this solution has and can learn to recognise situations specific to a company.

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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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• The user interface is in Flash, which can be very frustrating and slow at times. Apparently, this is to be transitioned in a future release.
• Can only segment the last 93 days of data. Any historical segmentation beyond the 93 days must be run in Explore (which is credit based, and has its own limitations with the number of credits per month, based on the initial contract with IBM).
• Reports can only display 93 days of data at a given time for custom date ranges. There are pre-programmed date ranges setup with IBM during implementation (last week, last month, last quarter etc.), but are not flexible enough to answer more specific questions.
• Certain reports cannot have segments applied, making answering some simple questions a bit more tricky. For example, I can create a segment around mobile devices and apply it to the marketing channels report, but I can't create a marketing channel segment and apply it to the mobile reports.
• Built in API calls allows for nice report design and automation.

• 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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IBM Digital Analytics is a great solution for our clients and I believe they offer the best solution for the retail space. We have access to IBM support via email or live chat and they can answer many of the reporting questions that come up. IBM is receptive to our feedback of the product so I am confident they will continue making improvements

Very easy to implement and use.

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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Never had any issues

As reports are templated, the system is pretty quick. Sometimes you have to wait a bit for a report to render. Or you might have to re-load the page. But there is no real issue here and the system is on par with other similar systems.

Overall, the level of support is very good and I would say it is a strong asset of the solution. However, you can sometimes feel that there is a difference of level among the support team.

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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Online training is really great. One of the best assets that they have. Lots of great videos, pop quizzes at the end of each module. Fantastic. Other tools have similar features, but not as good.

See previous comment: reading and understanding the encyclopedic implementation guide is a must.

Much of the work we did in IBM Digital Analytics could have been answered through Google Analytics, a much simpler, agile and FREE solution set. Not mention, given the vast number of Google Analytics USERS, free and actionable support is simply a click away ... this compared to IBM Digital Analytics fractured and often absent support service.

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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This solution can support large amount of data and transaction. The way that user management features are built, it shows it is meant for large organizations.

• We spend too much time trying to work around bugs on the new UI.
• We spend too much time trying to figure out how to make certain segments work because support and the knowledge center are lackluster.
• Our sales rep is very unresponsive and leaves us searching for a lot of answers on our own, including what other products we may benefit from that IBM offers.

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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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