Hortonworks Certified for Spring XD

Big Data announcements are coming from the Strata Conference + Hadoop World 2013 in New York this week from Hortonworks, Rainstor, and Appfluent. The event conversation can be followed on Twitter hashtag #strataconf.

Hortonworks certified for Spring XD

Hortonworks and Pivotal announced that Spring for Apache Hadoop, which is bundled with Spring XD, has been certified with Pivotal HD and Hortonworks HDP products. This certification enables Java developers to use modern and familiar tools to build big data applications that work across major Hadoop distributions without modification. Spring for Apache Hadoop (SHDP) aims to help simplify the development of Hadoop based applications by providing a consistent configuration and API across a wide range of Hadoop ecosystem projects such as Pig, Hive, and Cascading in addition to providing extensions to Spring Batch for orchestrating Hadoop based workflows.

“Spring XD connects big data apps to existing systems, as well as any new data source or data store – and will indeed appeal to the enterprise,” said Shaun Connolly, vice president, Corporate Strategy for Hortonworks.

Hortonworks also announced that its Hortonworks Data Platform (HDP) is now available for resale through HP. Built, integrated and tested by the core architects of Apache Hadoop, HDP includes the necessary components to help refine and explore new data sources, and find new business insights. HDP allows enterprise organizations to cost-effectively capture, process and share data in any format and at any scale. “This collaboration with HP will help customers and partners seamlessly incorporate Hadoop into their big data strategies and next-generation architectures,” said Shaun Connolly, vice president of corporate strategy, Hortonworks.

Rainstor validates database with EMC

Rainstor announced that it has successfully completed product testing, resulting in validation of its database on EMC Corporation’s Isilon Scale-Out network-attached storage (NAS) running on the Hadoop Distributed File System (HDFS). RainStor is already in production with customers running on Isilon, and by adding native Hadoop capabilities, customers gain further benefits and flexible deployment options with Big Data initiatives.

The RainStor highly-compressed file format is virtualized from the underlying storage layer and therefore behaves the same whether running on DAS or NAS. With the ability to co-exist Hadoop data running on both DAS and NAS, you can now separate the compute layer from the storage layer and gain both scale efficiencies and query performance.

“Isilon running on RainStor provides high-impact use cases, including a compliance data archive for years of history reaching petabyte scale,” said Sam Grocott, Vice President, Marketing and Product Management, EMC Isilon Storage Division.  “The one-two punch of RainStor and Hadoop on Isilon gives customers both performance and efficient scale with the added bonus of being easy to deploy and maintain. Case in point: RainStor and Isilon customer saw a 32X compression rate enabling efficient, predictable scale.”

Appfluent Visibility for Hadoop

Appfluent announced its groundbreaking new product, Appfluent Visibility for Hadoop. Giving insight into Hive SQL, Appfluent Visibility for Hadoop delivers detailed insight into the user activity related to Hive including the SQL statements, their performance and the data sets being used in Hadoop.

The solution also shows how the SQL statements correlate to the performance of associated MapReduce jobs, system resource consumption and performance.

"Hadoop has become a major disruptive force, with a rapidly growing number of large enterprises moving workload and data onto Hadoop to slash database infrastructure costs and extend analytic capabilities,” said Frank Gelbart, Chief Executive Officer of Appfluent. “Operations and development teams need a way to proactively discover causes for performance bottlenecks and respond to end-user issues.  Our solution gives them the in-depth, actionable information needed to allow them to quickly diagnose problems and increase performance levels.”