Joinutility seperatorLogin utility separator Infobright.com

Infobright Blog

25
Apr

Percona 2012 MySQL Conference

craigtrombly's photo
by craigtrombly     Wed, Apr 25, 2012

I had the chance to attend the MySQL Percona 2012 conference just a few shorts weeks ago in Santa Clara. The conference and expo were a three day event that focused on a variety of topics that ranged from performance and tuning to scaling and backup technologies. Although the attendance has been slightly diminishing over the last few years, I still felt that the demographics of the attendees were more defined. Among them were the software architects and engineers, database administrators and chief technology officers that were seeking ways of handling their normal day to day issues surrounding Big Data. Many of the attendees commented quite nicely about the presentations and the general tenor of the conference seemed very amicable.

Some of the most notable exhibitors had new open source technologies and frameworks that are starting to become noticeable. Companies like Sphinx, an open source search technology, had quite a few of their engineers at the show and were ecstatic about feedback they got from the attendees. Another growing company, Akiban, was also there to introduce their table grouping framework for speeding up queries. There was a bit of buzz around their booth because they had this Lego contest that attracted quite a few creative types, but even more so due to the up and coming release of their software to the open source world. Most of the MySQL database companies were present at the expo, along with a range of NoSQL and NewSQL technologies like NuoDB. On the hardware side of things, technologies like Fusion-io with their amazing speed and benchmarks were there enticing decision makers to test out their ioMemory and ioDrives. There was another young company, Virident, that looks like it may give Fusion-io a run for their money.

As the Community Manager, I had a goal to talk about the advantages of our open source software and try my best to tell attendees about our architecture. Oftentimes, I had approximately twenty seconds to do so, and I felt like I was successful. Though there were quite a few people I did not get a chance to speak with, of those with whom I did, the response was incredibly positive and even more so, exciting. I was impressed with the amount of knowledge that some people did have about our technology as well as excited to talk to those who knew little to none. Something else that I did find impressive though was the amount of energy in the room. There was certainly a high level of enthusiasm that felt good to be around, which I felt made for a great expo.

Overall, I found the conference to be hugely beneficial to the community because of the networking that it offered and a chance to identify new use cases with more companies. Amongst the hoopla, I was able to get a moment to walk through with my laptop and create a video of a few of the booths and talk with some of the exhibitors, so take a quick look when you get a chance. I cannot say that I did not have a lot of fun, because I certainly did, as well as get a chance to carry forward the message about our incredible architecture. Big "Ups" to Infobright for their decisions in bringing this technology to where we are and where we are going. See you guys in Portland at Oscon 2012...

Infobright     Tags: conference, mysql, percona

25
Apr

Solutions to our Solutions

Infobright
by Dan de Grazia     Wed, Apr 25, 2012

I am new to Infobright but I have been working on the problems we solve for many years This is the first of several blogs I plan to write on both business and technical issues, including one on how to get reliable results from a proof-of-concept.

Maybe it is the everyman IT story but it is so common that it has become part of the background noise of Big Data, particularly the problem of machine-generated data: it is the problem of finding a solution to our solution.

Most of us continue doing what we have done in the past until it doesn't work anymore. That seems pretty smart. And it is. However, once it stops working things get foggy quick. Big machine data problems are a classic example. Twenty and even ten years ago we were all doing fine, our existing hardware and row-based solutions were able to scale with the data volumes. We were working in a world where Moore's Law kept us out of trouble on the raw power side and disk manufactures kept innovating storage systems. We were IT and we were smart and we had money to spend.

For several reasons, such as data retention regulation and Internet access expansion, our money started to run out. More importantly we never considered that our needs would outstrip our growth curve. Ten years ago we were confident that Moore's Law would hold and it has. We never thought that our problems could grow faster than that. Well they did.

Here is where the real opportunity sets in (read big problems). We naturally think in terms of the tools we already have to find solutions to our problems. It is one of my worst habits, to go to my toolbox to see what I might have that fixes my problem, or more accurately that fits the solution I think I need. With Big Data we wanted a solution in the worst way. In many cases this is what we have. Studies show the top responses to big machine data analytics problems are: reduce the amount of data the user has access to, hire more DBAs and buy bigger, faster hardware. In some cases one quarter of our IT budget goes to storage. We did this knowing we were sinking faster than we were bailing. Same toolbox yields same tools.

Next week I am are going to discuss other technologies that attempt to add tools to the toolbox and why this is so hard to do. I do want to end with one last "new guy" insight from my beginnings at Infobright. Most people come to Infobright having already seen that applying standard thinking to their problem has failed. They now suspect they have the problem of looking for a solution to a solution they have already spent considerable time and money on. Infobright is what happens when serious problems are tackled by serious thinkers. In the realm of big machine data this means speed and compression go up and cost goes down. Until Infobright, everyone above was right; you were either small or you were powerful but you were not both – and low cost was never an option. As we will cover in the next few blogs we finally have a solution to our solution. Infobright.

Infobright     Tags: big+data

Next Page