Databases: Understanding Technologies and What They're Good For

As the data warehouse evolved beyond support for 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 immediate response time current information all stress the databases we've been using.

Many new platform technologies promise to replace databases entirely, but they rarely deliver on the promises, instead leading to technical project failures. The reasons for this go to the root of why we have databases and what their history is, what parallel data platform technologies are good for, and why we should or shouldn't use them.


Target Audience: Technical leaders, architects, database and analytics professionals who make platform decisions
Prerequisites: Understanding of databases, BI and analytic workloads
Level: Advanced

Extended Abstract
'As the data warehouse evolved beyond support for 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 immediate response time current information all stress the databases we've been using.

Many new platform technologies promise to replace databases entirely, but they rarely deliver on the promises, instead leading to technical project failures. The reasons for this go to the root of why we have databases and what their history is, what parallel data platform technologies are good for, and why we should or shouldn't use them.

Analytic databases and parallel platforms are also designed to meet these needs. Specialized databases and hardware promise to solve problems of scalability, performance, or analytic requirements. However, there are many tradeoffs to consider when evaluating these products that aren't highlighted in their sales presentations.

This session will provide a review of technology and systems powering the data platform landscape --from analytic databases and columnar databases to massively parallel processing, nosql, 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.