Three Things Making Life Tough for Your RDBMS
Relational database management systems (RDBMS) undoubtedly still have a place and function in modern business. However, the RDBMS has not been able to step up in the face of changing business demands for applications with massive scale requirements providing in-the-moment interactions with geographically distributed users.
Cloud applications are flooding our digital world, and the highly distributed, contextual, scalable, always-on, real-time nature of these applications is making life extremely difficult for relational databases to handle their requirements.
Specifically, here are three of the things that are making it almost impossible for enterprises to survive on a relational database alone:
Changing data models
As more and more semi-structured and unstructured data flood our world and software systems, it gets harder and harder to rely on only a relational database to analyze this data.
Relational database schemas are good for legacy transactional applications but are having a tough time meeting the rapidly evolving analytics needs of most enterprises, which need to relate data in ways they never did before.
Only industry-leading NoSQL databases designed to handle different data model types – from graph to JSON to document to column – can offer an unheralded degree of flexibility and agility in the way your IT teams and/or engineers use and analyze your data.
Massive scale for operational data
Data today is exploding exponentially, putting incredible stress on your database. Relational databases have a much harder time responding to scale in real-time than a NoSQL database with a masterless architecture.
It’s not so much that they can’t scale, it’s that they’re much more expensive and complicated to scale, because they generally scale up with the addition of hardware instead of scaling OUT, like a masterless architecture NoSQL database, by spreading capacity across commodity servers to handle the zillions of operational transactions every minute
In an age where data generated by users and machine transactions surge regularly, your enterprise needs more than just an RDBMS to respond.
Zero tolerance for downtime
More and more cloud applications are becoming core to the business making downtime a no-go for database managers.
No longer do DBAs have the pleasure and privilege of updating their data overnight so that a customer can get his/her product recommendation or account update the next day. It now has to happen IMMEDIATELY so that the customer has immediate insights and can maneuver his/her current purchase, service request, or download without delay.
In today’s cloud-based, big data world, you don’t need just high availability, you need continuous availability.
It is not about five 9s or 99.99999% – it’s about 100% uptime. Delivering 24-7 availability is enormously hard for relational databases because they’re usually deployed to a single physical server or rely on clustering with shared storage. This means that if the shared storage or master server fails, the whole database goes down.
A masterless NoSQL database, on the other hand, partitions data to multiple database instances with no shared resources and uses tools like advanced replication to ensure the database can seamlessly switch to other nodes if one node fails.
The Bottom Line
To function properly in today’s fast-paced, data-driven world, your enterprise needs more than just to be able to reliably store and process a large amount of structured and unstructured operational data. It needs to be able to analyze this data in real time for real-time insights, and that can only be done with a database that is solid yet nimble and able to handle various data models, massive scale, and continuous availability. Read this ebook to learn why your RDBMS fails at scale.
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