IBM watsonx.data vs. Nasuni

Real-time transaction processing (both reads and writes) is where DataStax Enterprise shines. It's very fast with linear scalability should more resources be needed. Additional nodes are added very easily. DataStax Enterprise on its own (without Solr or Spark enabled) isn't well suited for long complicated reports. The data model doesn't support joining multiple tables together which is common in BI reporting.

Well suited if you have a lot of data that doesn't need to be stored and read right away. I think even if you don't have much data, you can still use it for it's intended purpose to great effect, but think of it as the more data you have, the even better it will work. I don't think it would be particularly useful if you already have a slick file restore system in place and you don't need to store your data elsewhere with redundancy.

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• Datastax Cassandra provides high availability and good performance for a database. It is built on top of open source Apache Cassandra so you can always somewhat understand the internal functioning and why.
• Datastax Cassandra is fairly simple to start using, you can install/setup your cluster and be productive in 1 day.
• Datastax Cassandra provides a lot of good detailed documentation, and when starting, the detailed free videos on the Datastax site and documentation are very helpful.
• Datastax Enterprise Edition of Cassandra provides more tools, good support, and quick response SLA for enterprise business support.

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• The management console is extremely simple and easy to navigate, making common tasks easy to do.
• Our storage appliance is configured to snapshot data several times an hour, making the risk of data loss very low.
• Data restores are very intuitive, and take seconds to initiate regardless of whether it is one file or 300GB of data. We have successfully restored many Gigs of data in minutes.

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• Interface do need some improvement to be more intuitive for analysts like me.
• Configuring multiple data sources can require support, as it isn't easy for new users. So, it can be made easier.
• Additional ETL features can be added, so users don't have to switch between tools.

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• Better analytics when issues arise.
• Better onboarding documentation.
• Real-time monitoring.

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As an open source technology Cassandra can be readily used with or without any commercial support. DataStax provides value-added services and features, and in the end it is up to individual situations to strike a balance between the desirability of such support/service versus the associated cost.

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DataStax has a good community built around it and has amazing scalability options. Though the initial setup is a bit costly, in the long run, it makes up for it. It also has powerful monitoring tools and a clean UI.

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As I mentioned, the user interface is amazing and straight forward. It's very easy to learn how to configure and restore files. I would like a bit more reporting, especially in terms of live reporting and monitoring. The support is great when you have a question on how to do something, which helps with usability.

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good recovery features

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scalable product

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Again, it may have a little to do with the size and speed of your own environment, but we've been nothing but pleased with the speed of access of the files - even pulling old files from the cloud storage. Recovery of huge and many data files is a bit slow if you don't have the specs of the filer up to snuff.

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We have had a few situations where we caused an outage or something has gone wrong and we are able to get a support person to offer live help within minutes. The escalation process is excellent - the best I've seen - and the support team is incredibly strong. Outside of emergencies, the team is very helpful with general questions and working through data model exercises and the subscription I believe still comes with some hours to help get the data model reviewed.

easy to follow documentation, support is there when needed

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use saas service

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Claude is better for troubleshooting actual OPS/REXX but that's not an IBM product so I understand why IBM watsonx.data isn't great for that, but if IBM watsonx.data did help with code then it would be the only product that I use.

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The technical support and escalation path for Nasuni is much more reliable and efficient. No getting transferred to various teams. Often times, the person who answers your call is able to resolve your issue. If they cannot, they get the case assigned to the appropriate engineer right away. Time to close has always been very good.

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cognos integration works great

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• for one automation project, we managed to cut cloud storage costs by a third through IBM watsonx.data's lakehouse optimization
• data integration projects have had a 20 % reduction in turnaround times. Can only imagine how that will improve with the Claude partnership

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• Dramatically reduced time spent managing our storage platform. Quotas and reporting tools take all the guesswork out of data growth. Updates are easy to deploy. Time freed up can be used for more user-facing activities that we consider more valuable to the organization.
• The overall stability of the platform has been very good. We have been running on the same hardware for the past four years without any performance issues.

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