In-memory technology has been around for quite some time but developing backend architectures that optimize memory first for modern applications is just starting to become predominantly acknowledged as a prudent approach. Why is this so optimal?
Find out and learn much more about in-memory computing at the relaunch of the "Bay Area In-Memory Computing Meetup" June 13 from 6:30-8:30 p.m. at Sophia University in Palo Alto, Calif. Register here: Bay Area In-Memory Computing Meetup. We'll have pizzas, beverages, cool t-shirts and a raffle for a Google Home! The talk is titled, "Intro to Apache® Ignite™ (a.k.a. In-Memory Computing 101)."
OK, I'll give you a sneak peek of my talk by addressing my question above. If we consider the sheer timeframe it takes to write to the database itself with I/O as a bottleneck and if we can eliminate that by hitting the cache first, we have some serious performance gains. Further, if we can employ this strategy in a distributed fashion we can make our transactional experience much more performant because we aren’t adding the additional latencies cause by I/O and database transactions if we can operate purely from our cache store. With Apache Ignite, which utilizes a scalable, peer to peer architecture, relational and NoSQL database backends can become much more performant.
In my introductory talk, I am going to be discussing my findings coming from a database background and specifically how the transition has been. I will talk about the general use cases, what Apache® Ignite™ includes out of the box and how it can be leveraged to expedite sluggish transactions. In my talk, I will give resources about how to setup Apache Ignite and get started with the community so you can engage with the experts. I hope you come and enjoy some pizza with the Ignite folks!
When: June 13, 6:30-8:30 p.m.
Where: Sophia University,1069 East Meadow Circle, Palo Alto, CA
About the tech in the talk: Apache® Ignite™ is an in-memory computing platform that delivers unprecedented speed and unlimited scale to modern data processing. It enables high-performance transactions, real-time streaming, and fast analytics in a single, comprehensive data access and processing layer.