Cloudera Engineering Blog · CDH Posts
The Only Full Lifecycle Management for Apache Hadoop: Introducing Cloudera Enterprise 3.5 and SCM Express
Drew O’Brien is a product marketing manager at Cloudera
We’re excited to share the news about the immediate availability of Cloudera Enterprise 3.5 and SCM Express, which we announced this week in tandem with our presence at Hadoop Summit. These products represent a major advance in Cloudera’s mission to drive massive enterprise adoption of 100% open source Apache Hadoop. We now make it easier and more convenient than ever before for companies to run and manage Apache Hadoop clusters throughout their entire operational lifecycle.
Ed Albanese leads business development for Cloudera. He is responsible for identifying new markets, revenue opportunities and strategic alliances for the company.
This week’s announcement about the availability of the Cloudera Connector for IBM Netezza is the achievement of a major milestone, but not necessarily the one you might expect. It’s not just the delivery of a useful software component; it’s also the introduction of a new generation of data management architectures. For literally decades, data management architecture consisted of RDBMS, a BI tool and an ETL engine. Those three components assembled together gave you a bonafide data management environment. That architecture has been relevant for long enough to withstand the onslaught of data driven by the introduction of ERP, the rise and fall of client/server and several versions of web architecture. But the machines are unrelenting. They keep generating data. And there’s not just more of it, there is more you can—and often need—to do with it.
The times they are a-changin’, and unstructured data is taking over
Bala Venkatrao is the director of product management at Cloudera.
I had the pleasure of attending Enzee Universe 2011 User Conference this week (June 20-22) in Boston. The conference was very well organized and was attended by well over 1000+ attendees, many of whom lead the Data Warehouse/Data Management functions for their companies. This was Netezza’s largest conference so far in seven years. Netezza is known for enterprise data warehousing, and in fact, they pioneered the concept of the data warehouse appliance. Netezza is a success story: since its founding in 2000, Netezza has seen a steady growth in customers and revenues and last year (2010), IBM acquired Netezza for a whopping $1.7B.
I recently gave a talk at the LA Hadoop User Group about Apache HBase Do’s and Don’ts. The audience was excellent and had very informed and well articulated questions. Jody from Shopzilla was an excellent host and I owe him a big thanks for giving the opportunity to speak with over 60 LA Hadoopers. Since not everyone lives in LA or could make it to the meetup, I’ve summarized some of the salient points here. For those of you with a busy day, here’s the tl;dr:
I am very pleased to announce the general availability of Cloudera’s Distribution including Apache Hadoop, version 3. We’ve been working on this release for more than a year — our initial beta release was on March 24 of 2010, and we’ve made a number of enhancements to the software in the intervening months. This release is the culmination of that long process. It includes the hard work of the broad Apache Hadoop community and the entire team here at Cloudera.
We’ve done three things in this release that I’m particularly proud of.
On Monday, we held our second Flume Office Hours at Cloudera HQ in Palo Alto. The intent was to meet informally, to talk about what’s new, to answer questions, and to get feedback from the community to help prioritize features for future releases.
Below is the slide deck from Flume Office Hours:
Cloudera is happy to announce the fourth beta release of Cloudera’s Distribution for Apache Hadoop version 3 — CDH3b4. As usual, we’d like to share a few highlights from this release.
Since this will be the last beta before we designate CDH3 stable, our focuses for this release have been on stability, security, and scalability.
A common question on the Apache Hadoop mailing lists is what’s going on with availability? This post takes a look at availability in the context of Hadoop, gives an overview of the work in progress and where things are headed.
When discussing Hadoop availability people often start with the NameNode since it is a single point of failure (SPOF) in HDFS, and most components in the Hadoop ecosystem (MapReduce, Apache HBase, Apache Pig, Apache Hive etc) rely on HDFS directly, and are therefore limited by its availability. However, Hadoop availability is a larger, more general issue, so it’s helpful to establish some context before diving in.