InfoSphere BigInsights 2.1*
BigInsights 2.1 contains enhanced functionality and improved consumability, making it easier to use Hadoop leveraging existing skills, build big data applications and uncover insights in your data.
- Big SQL - With Big SQL, a SQL interface for Hadoop, you can access data in BigInsights without having to learn a new programming language.
- GPFS-FPO - With GPFS-FPO (General Parallel File System- File Placement Optimizer) support, you get an alternative file system to HDFS that brings POSIX compliance, no single point of failure and enhanced security.
- High Availability - With NameNode and JobTracker High Availability, you get an out of the box solution that eliminates admin intervention and reduces downtime by providing seamless, transparent and automatic failover.
Ask Bigger Questions
Cloudera develops open-source software for a world dependent on Big Data. With Cloudera, businesses and other organizations can now interact with the world's largest data sets at the speed of thought — and ask bigger questions in the pursuit of discovering something incredible.
Expand the Productivity and Possibilities of Hadoop
Apache Hadoop’s reliance on advanced languages and programming frameworks have limited its cost-effectiveness and adoption in many organizations. Pivotal HD Enterprise offers enterprise-hardened Hadoop, as well as advanced SQL query services that make Hadoop more stable and usable. The result: Reduced implementation costs for all but the most sophisticated organizations.
Pivotal Advanced Database Services, powered by HAWQ, add SQL’s expressive power to Hadoop. By adding rich, mature SQL processing, Pivotal HD leverages existing BI and analytics products and your workforce’s SQL skills to simplify development, expand Hadoop’s capabilities, increase productivity, and cut costs.
The Apache™ Hadoop® project develops open-source software for reliable, scalable, distributed computing.
The Apache Hadoop software library is a framework that allows for the distributed processing of large data sets across clusters of computers using simple programming models. It is designed to scale up from single servers to thousands of machines, each offering local computation and storage. Rather than rely on hardware to deliver high-avaiability, the library itself is designed to detect and handle failures at the application layer, so delivering a highly-availabile service on top of a cluster of computers, each of which may be prone to failures.
The project includes these modules:
- Hadoop Common: The common utilities that support the other Hadoop modules.
- Hadoop Distributed File System (HDFS™): A distributed file system that provides high-throughput access to application data.
- Hadoop YARN: A framework for job scheduling and cluster resource management.
- Hadoop MapReduce: A YARN-based system for parallel processing of large data sets.
Hortonworks Data Platform
Hortonworks Data Platform (HDP) is a pure open source Apache Hadoop distribution. It is ideal for organizations that want to combine the power and cost-effectiveness of Apache Hadoop with the advanced services and reliability required for enterprise deployments.
The Intel® Distribution for Apache Hadoop* Software
MapR delivers on the promise of Hadoop, making managing and analyzing Big Data a reality for more business users. The award-winning MapR Distribution brings unprecedented dependability, speed and ease-of-use to Hadoop.
SpatialHadoop is an open source MapReduce framework designed specifically to handle huge datasets of spatial data. SpatialHadoop is shipped with built-in spatial high level language, spatial data types, spatial indexes and efficient spatial operations.