As the data warehouse evolves beyond support for simple queries and batch reports, supporting new workloads might seem hopeless due to limited performance and scalability. More data, increasingly complex analysis, and the need for fast queries on up-to-date information all stress the databases we've been using for BI. Many new database technologies from the big data market promise to replace databases entirely, but they rarely deliver on the promises. The reasons for this go to the root of why we have databases and what their history is, what big data platform technologies are good for, and why we should or shouldn't use them.
Analytics databases and data warehouse appliances are also designed to meet these needs. Specialized databases and hardware promise to solve problems of scalability, performance, or analytics requirements. However, there are many factors to consider when evaluating these products that aren’t highlighted during their sales presentations.
This session will provide a review of the technology and systems powering the big data and database landscape—from data warehouse appliances and columnar databases to massively parallel processing and in-memory technology. The goal is to help you understand the strengths and limitations of the underlying technologies so you know what the vendors are selling. This will help you navigate the options available so you can find the technology best suited to your needs.
You Will Learn
- What hardware and software technologies are available and how they work
- What the different technologies are good for
- How to decide what to use for different workloads