Data is growing and evolving in ways that legacy architects could not have imagined. We are seeing a shift from systems of record that are highly autonomous and rigorously constructed to make sure every piece of data is processed in-tact to data platforms that throw caution to the wind in exchange for performance and scalability. As data evolves and becomes more complex it begs the question, “What type of relationship are you seeking with your database?”
The answer is often more complicated than a single solution a vendor can provide, which is why it’s increasingly important to weigh the costs and benefits of any data platforms and also examine the implications of implementing it with your existing system. Then users can move forward with a new data initiative with the confidence that they will be able to focus on the innovative aspects of the technology rather than deployment, implementation and troubleshooting.
J.R. Arredondo takes us through a model of considerations all aimed at using the right tool for the right job. Each new data platform has advantages and limitations. By knowing whether you need transactional scaling vs. analytics, or a flexible schema database vs. an in-memory solution may help ensure you don’t waste cycles focusing on the wrong technology.
Join us as we dive into these areas of consideration and some real world use cases of how a company can leverage multiple data platforms to achieve a variety of valuable use cases.