The organizers of the Craft Conference (http://craft-conf.com/2014/) have joined forces with some of the best Budapest meetups to organize a Meetup Evening as a warmup event, and guess what, the Craft guest speakers are going to be there, too!
Each meetup will have a different guest, you can find the list and the speakers schedule on the Craft site. (http://craft-conf.com/2014/#meetups) All events are free to visit for anyone. Meetups will open gates at 6PM, we provide pizza and drinks, and the talks will start from 6:30PM. The attendees will get two coupons, which can be redeemed at Anker't (http://ankert.hu/) (google maps (https://www.google.co.uk/maps/place/Paulay+Edefirstname.lastname@example.org,19.0590815,17z/data=!3m1!4b1!4m2!3m1!1s0x4741dc6bc3b9503f:0x7d3e93d5d01f296d)) after the meetup for beer, wine or fröccs. (http://en.wikipedia.org/wiki/Spritzer)"
We are co-hosting our event with the Budapest Database Meetup (http://www.meetup.com/Budapest-Database-Meetup/) group, so when all the seats are gone over here you can check their event (http://www.meetup.com/Budapest-Database-Meetup/events/178044682/) as well. No double RSVP needed! If you are checked in either to our event or theirs you are good to go. Please be so kind and take the RSVP seriously this time.
RAMCloud: Low-latency DRAM-based storage
Diego Ongaro @ongardie (https://twitter.com/ongardie)
This talk will give an overview of RAMCloud, a scalable, high-performance, general-purpose storage system which keeps all data in DRAM at all times. Our goal is to make it easy for developers to harness the full performance potential of large-scale DRAM storage. RAMCloud fetches data in 5-10 microseconds, it's durable and available, and it's designed to scale to thousands of servers. If successful, RAMCloud will enable new applications that manipulate large-scale datasets much more intensively than has ever been possible before.
Using MySQL as a pseudo-NoSQL Database
Bjorn Freeman-Benson @bjorn_fb (https://twitter.com/bjorn_fb)
Abstract: In the early minimum-viable-product days of New Relic, we decided to focus on building our product rather than building a custom time-series database and thus we used MySQL for storing not only normal relational data (users, accounts, invoices, etc) but also for what you think of as NoSQL data. This decision has held up remarkably well as we now have almost 100,000 accounts reporting billions of metrics every day and we're still using MySQL. I'll talk a little about some of the tricks that we've used to do this including some of our sharding decisions (pro and con) and some of the ways we've learned to create and use indexes.