Simplifying Data Architecture: Why Use Multiple Datastores When You Can Use Just One?
Facing unnecessary architectural complexity? Too many moving parts? If these are problems you’re facing, then this calls for architectural simplification.
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Why use multiple datastores when you can use just one?
As more optimistic economic conditions emerge after the pandemic, organisations need a single, real-time view of accurate and reliable data so they can deliver value to customers, reduce risk and respond rapidly to new opportunities and challenges.
However that’s far from easy, a common challenge we hear from many organisations is that over the years they have accumulated multiple and diverse technologies to manage different types of data and workload. This has left them facing unnecessary architectural complexity and latency, as well as dealing with many moving parts. This calls for architectural simplification.
To explain more, Director of Product Management, @Jeff Fried spoke at a recent IASA (Irish Computer Society) event about the different methods in which you can simplify your data architecture. The routes, all of which deliver reduced costs, increased performance, and improved security, include:
- Adopting a multi-model database
- Deploying a translytical data platform
- Capitalising on in-database machine learning
If you missed it, you can hear from Jeff on the pros and cons and the trends to help you understand what is possible with multi-workload and multi-model databases, listen to his free on-demand webinar or read his recent blog.
Want to discuss?
Please feel free to share your thoughts in the comments to this post. Stay tuned!
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