Tuning In-memory Databases

In-memory databases have now become permanent components of the enterprise application stack, and knowing how to size, scale, and tune them in VMware vSphere or bare metal environments is a paramount skillset. In recent years, we have seen in-memory cluster sizes from 1 to 5 TB of memory within a single cluster driving millions of transactions per day. Not only do these systems have zero tolerance to failure, most expect a predictable throughput and response time. In this session, we visit the most common deployment patterns and what choices you have to make in placing the server components vs. the consumption/ingestion clients. We will also inspect various transaction volumes and discuss common administration tasks.

This session will do a sizing deep dive, in terms of how to best size the cache nodes, how to size the virtual environment, and other considerations to make these systems highly available, scalable and with predictable performance. In the case of Java based in memory DBs we will do a deep dive into various GC algorithms and how to best configure JVMs.