A correctly setup Hadoop cluster can analyze a human genome in hours, while a poorly optimized one will take days and use twice as many nodes. Although Hadoop is a free product, potential issues are many. Even a slight error in your algorithm can introduce significant inaccuracies into end results. Other common pitfalls include the peculiarities of different OS’s and distributions, problems with assembling clusters, virtualization, etc.
Speed up Big Data Analysis with Hadoop-based Distributed Processing
Scale to petabytes of data and hundreds of nodes
Serving leading technology vendors, such as Joyent, Couchbase, RightScale, and others, Altoros helps to implement scalable Hadoop-based solutions for data mining, analysis, visualization, etc.
Build and fine-tune large Hadoop clusters
Assemble, deploy, test, and optimize efficient Hadoop clusters of any size and complexity
Create advanced algorithms
Design algorithms for distributed computing of custom processes
Achieve endless scalability
Build distributed systems that can easily scale to petabytes of data and hundreds of nodes
Implement process automation
Automate deployment, administration, and performance monitoring of large Hadoop clusters
Hadoop-based solutions from cluster monitoring to machine learning:
- Building complex systems since 2001, Altoros has proven expertise in Hadoop-based data processing tools, such as Mahout, Hive, Pig, Chukwa, Oozie, ZooKeeper, etc.
- 20+ successfully deployed Hadoop clusters: the largest one of them consists of 400+ nodes.
- You’ll get access to 100+ professional data scientists who work for the most reputable universities in Eastern Europe. Our engineers can work both onsite and offshore according to your project needs.
- Our R&D engineers performed multiple benchmark studies of Hadoop implementations, NoSQL databases, and cloud systems published by CIO.com, NetworkWorld, ComputerWorld, TechWorld, and other industry magazines.