Astra DB, now part of IBM watsonx.data vs. Microsoft Copilot Studio

We've been super happy with Astra DB. It's been extremely well-suited for our vector search needs as described in previous responses. With Astra DB’s high-performance vector search, Maester’s AI dynamically optimizes responses in real-time, adapting to new user interactions without requiring costly retraining cycles.

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It has performed exceptionally well where I have required deep contextual understanding , multi deimension analysis or web research. Recently it helped me in the implementation of SAP Project. It helped to prepare documentation like business blue prints, conduct workshops. Understand business requirement with the help of reviewing the information by summarizing.

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• We need to be able to process a lot of data (our biggest clients process hundreds of milions of transactions every month). However, it is not only the amount of data, it is also an unpredictable patterns with spikes occuring at different points of time - something athat Astra is great at.
• Our processing needs to be extremaly fast. Some of our clients use our enrichment in a synchronous way, meaning that any delay in processing is holding up the whole transaction lifecycle and can have a major impact on the client. Astra is very fast.
• A close collaboration with GCP makes our life very easy. All of our technology sits in Google Cloud, so having Astra in there makes it a no-brainer solution for us.

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• Agentic workflows
• AI chatbots
• Deploying via Teams
• Multiple knowledge sources

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• Need better fine-grained Security options.
• The support team sometimes requires the escalate button pressed on tickets, to get timely responses. I will say, once the ticket is escalated, action is taken.
• They require better documentation on the migration of data. The three primary methods for migrating large data volumes are bulk, Cassandra Data Migrator, and ZDM (Zero Downtime Migration Utility). Over time I have become very familiar will all three of these methods; however, through working with the Services team and the support team, it seemed like we were breaking new ground. I feel if the utilities were better documented and included some examples and/or use cases from large data migrations; this process would have been easier. One lesson learned is you likely need to migrate your application servers to the same cloud provider you host Astra on; otherwise, the latency is too large for latency-sensitive applications.

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• Ability to combine multiple sources in one query (indexing)
• SharePoint integration - word count limit detrimental
• Clearer communication and understanding of features and limitations

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At first, it stands out in integrating with the Microsoft ecosystem like Teams, Word, and Outlook. It makes simple for creation and deployment of AI agents and tools with out heavy coding. Great for the purpose of creating AI chat bots for regular tasks. It is excellent for quickly running mock demos.

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It's a great product but suffers with counters. This isn't a deal breaker but lets down what is otherwise a good all round solution

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I would give 9 as it works well for us by utilizing the agentic part we are able to utilize the capabilities of copilot studio, If the billing structure and hallucinations can be corrected I would have given 10 as well. I would recommend everyone to give it a try if you want to up your game in Agentic AI with clients.

No performance issue till date.

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Independently Invited by TrustRadius

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Their response time is fast, in case you do not contact them during business hours, they give a very good follow-up to your case. They also facilitate video calls if necessary for debugging.

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A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

We had an excellent experience during the online training of Microsoft Copilot Studio. We were given training which included complete informations in the session. The session include the how we can use it. It gave us the complete guide. We had recorded sessions for future reference.

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Graph, search, analytics, administration, developer tooling, and monitoring are all incorporated into a single platform by Astra DB. Mongo Db is a self-managed infrastructure. Astra DB has Wide column store and Mongo DB has Document store. The best thing is that Astra DB operates on Java while Mongo DB operates on C++

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It is worldwide accepted and we already have the workspace and other tools from Microsoft family which compels us to go for copilot rather than google as it gives you wide range to explore in other areas in the same workspace. Rating and worldwide acceptance is more for Microsoft when compared to any other tool with respect to Agentic AI platform.

We are well aware of the Cassandra architecture and familiar with the open source tooling that Datastax provides the industry (K8sSandra / Stargate) to scale Cassandra on Kubernetes.

Having prior knowledge of Cassandra / Kubernetes means we know that under the hood Astra is built on infinitely scalable technologies. We trust that the foundations that Astra is built on will scale so we know Astra will scale.

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As it is low code it empowers everyone even with non technical person to create and deploy and publish the custom agents. Then agents can operate and plan, learn and scale the complex and challenging tasks across the entire business process. It helps to connect with data and take respective action.

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Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

Not used.

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Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info

• Better uptime due to the managed service having no outages
• Less technical debt because we don't need to worry about upgrading our Cassandra clusters
• Lower cost on infrastructure as a whole
• Quick and easy to integrate vector search into our tech stack

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Invited by the Vendor

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• Speed of delivery
• Scale of deployment
• Increase of access

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Independently Invited by TrustRadius

A de minimis incentive was given to thank the reviewer for their time. The incentive was not used to bias or drive a particular response, nor was the incentive contingent on a positive endorsement. More Info