Like the title says, to choose an enterprise-level Massive Parallel Processing (MPP) database is actually a big headache for every Data Science Manager; basically because there are very good choices around the tech world.
Many of you, my good Data Science fellows should be hearing about Real-Time since from several years before, but we are in the Era of Information, and in the years of Big Data, and changes happens so quickly that you need to adapt very fast to support the big wave of information. In Analytics, it’s happening the same thing: because if you can answer smarter questions in seconds, you will be able to react quicker to these changes and that’s really matters in these rush times, my dear friends.
I was reading yesterday a great blog post from Derrick Harris, the well known technology journalist from GigaOM where he exposed some good points about Spark, the great technology which is been developed by AMLab from the University of California, Berkeley. But it’s not just Spark, there are some good pieces of technology which are disrupting Analytics field for good. I will try to put you some of my favorite platforms in this post, but I don’t want to repeat information, so I will write just little things and amazing quotes of each platform. Let’s begin. Continue reading “Why Real-Time Analytics matters”
HBase 0.96 is synonym of speed, better compression and high performance
The HBase development team is doing in these days a great job, adding some rock-solid features to this amazing data store. The next release will be 0.96, and it brings great things which I discuss with you righ now. I will expose you here the best features based on my own opinion; I’m open to discussion, so, let a comment to enrich the blog post if you want. OK, let’s start the engine. Continue reading “Some upcoming features in HBase 0.96”
Column-based data stores are becoming in an important trend today
If you read my post about Real-Time Analytics, you should be excited like me about this trend. Did you remember the phrase: “Time is equal to money”? Time is the main cause behind all innovations in the Database world: we want faster solutions; quick ways to gather huge quantity of data; faster ways to query billions of records; faster ways to adapt our infrastructure, etc; and many have tried to give clean and useful solutions to this problem.