6 min read
This quarter is shaping up to be a great one for MapR! After recently announcing record growth in the first quarterwe’ve got some great momentum going into the second.
Vertica on MapR SQL-on-Hadoop is now generally available, we're taking Apache Spark on the road, we've launched Developer Central and had an ecosystem and product update. Read below for more details.
Vertica on MapR SQL-on-Hadoop is generally available
This joint solution tightly integrates HP Vertica’s 100% ANSI SQL, high-performance big data analytics platform with the MapR enterprise-grade Distribution for Apache Hadoop, providing customers and partners with a high performing solution for operational and exploratory analytics with the lowest total cost of ownership (TCO). Learn More >
Join HP Vertica and MapR on Tuesday, June 3rd, at 9am PT/ 12pm ET, to learn how you can enjoy the benefits of a SQL-on-Hadoop. **Register Now >**
Product Updates & Announcements
The newly launched Developer Central is a place just for the developer community. Full of code samples and best practices, Developer Central will help you get started on Hadoop and manage your clusters efficiently. Read More >
MapR v3.0.3 Released
Hadoop Ecosystem Updates
Top Blog Posts
Big data has evolved to the 10 V's. These V-based characterizations represent ten different challenges associated with the main tasks involving big data. Read More >
The open source incubator project Apache Drill is well on its way towards its next big milestone. We’d like to share the great progress the Drill community has been making on the project, and outline the next steps for meeting the 1.0 beta release. Read More >
Together, MapR and our partners help organizations like yours make sense of your ever-expanding variety and volume of unstructured, semi-structured, and structured data. Check out our upcoming webinars to discover how you can get more from Hadoop.
Friday, May 16, 2014 at 10:00 am PT / 1:00 pm ET
Join authors and Mahout committers, Ted Dunning and Ellen Friedman, for an informative webinar on machine learning, with a focus on making it easy to build a recommendation system. Watch on-demand now >
Wednesday, May 21, 2014 at 9:00 am PT / 12:00 pm ET
In this webinar with MicroStategy, we will explore how Hadoop can produce easily translatable and integrated data, how BI tools can transform data into insight, and how the next-generation analytics and data platform can help you derive intelligent answers to your most critical business questions. Register Now >
Wednesday, May 14, 2014 at 11:00 am PT / 2:00 pm ET
All attendees will receive a $5 Starbucks gift card.
Join OnX for a live webcast featuring renowned big data expert Phil Simon as he shares big data stories from real businesses and the tangible, hype-free considerations you need to know to succeed. Register Now >
MapR in the News
MapR announced that first quarter bookings for its distribution of Hadoop since last year have tripled and that one of its customers has generated more than $1 billion of revenue using MapR Hadoop. Read More >
Apache Spark Tour
Join us to learn about Apache Spark and how you can run programs 10-100x faster on Hadoop. We're speaking at meetups in 10 cities, starting with Westlake Village (LA), St. Louis and Menlo Park, CA in May. Others are listed here.
Machine learning, large scale data analytics, Apache Hadoop, NoSQL databases, and much more are coming this May. No matter what you’re interested in, we have a schedule jammed packed full of great events for you. View our list of upcoming events >
**Hadoop Cluster Administration on MapR **Sunnyvale, CA, May 28-30
Learn MapR system administrator concepts and practices such as: planning, installation and configuration, load balancing and tuning, as well as diagnosing and solving problems in your Hadoop deployment. Sign up >
The primary objective of the training is to understand how to write effective MapReduce applications in Java. The course also covers debugging, managing jobs, improving performance, working with custom data, managing workflows, and using other programming languages for MapReduce.