In-Memory Performance at the Cost of Flash

Albert 2-3

Reducing the number of data stack layers and incorporating real-time data processing engines which utilize CPU parallelism enables bare-metal application performance, running millions of application ops/sec per node with unprecedented latencies. Using flash as in-memory can substantially reduce costs and be extremely fast, but we only see a fraction of that speed when we layer OS abstractions, middleware and apps on top, forcing us to use a lot more hardware resources and settling for high and unpredictable latencies. Yaron Haviv will introduce this new architecture approach and present a smart mobility case study which illustrates how a major ride-hailing company achieved in-memory performance at the cost of flash with a parallel processing engine. Participants will learn how to utilize flash beyond storage without compromising speed.

Profile picture for user
Yaron Haviv is a serial entrepreneur who has deep technological experience in the fields of big data, cloud, storage and networking. Prior to iguazio, Yaron was the Vice President of Datacenter Solutions at Mellanox, where he led technology innovation, software development and solution integrations. He was also the CTO and Vice President of R&D at Voltaire, a high performance computing, IO and networking company. Yaron is a CNCF member and one of the authors in the CNCF working group. He tweets as @yaronhaviv.