As businesses grow, many applications will, at some point, run into scaling issues — what works fine at low transaction volumes doesn’t work well, or at all, at high volumes.

In-memory technology solutions like the open-source Hazelcast Platform have helped many businesses overcome their scaling issues to provide high throughput and low latency at tremendous scale. But even among long-time users of the platform, there is a tendency to focus on the in-memory storage (or caching) aspects of the solution.

In this talk, we’ll focus on how in-memory compute APIs help leverage the processing capabilities of a distributed cluster, so you aren’t leaving large potential performance gains on the table. The combination of in-memory storage and in-memory compute provides a unique synergy that enables applications to address real-time use cases at any scale.