Concurrent, Inc., a leader in data application infrastructure, and Elasticsearch, Inc., provider of an end-to-end real-time search and analytics stack, has announced a partnership to accelerate the time to market for Hadoop-based enterprise data applications.
Enterprises seeking to make the most out of their Big Data can now easily build applications with Cascading that read and write directly to Elasticsearch, a search and analytics engine that makes data available for search and analysis in a matter of seconds. Once data is in Elasticsearch, users can also take advantage of Kibana, Elasticsearch’s data visualization tool, to generate pie charts, bar graphs, scatter plots and histograms that allow them to easily explore and extract insights from their data.
We’re on a mission to make massive amounts of data usable for businesses everywhere, so it’s no surprise that we’re teaming up with Concurrent, a company that’s leading the way in Big Data application infrastructure for the enterprise,” said Shay Banon, co-founder and CTO, Elasticsearch, Inc. “Now, when developers use Cascading to build Hadoop-based applications, they can easily utilize Elasticsearch to instantly query and analyze their data, allowing them to provide a fast and robust search experience, as well as gain valuable insights.”
As enterprises continue to heavily invest in the building of data-centric applications to connect business strategy to data, they need a reliable and repeatable way to consistently deliver data products to customers. With more than 175,000 downloads a month, Cascading is the enterprise development framework of choice and has become the de-facto standard for building data-centric applications. With a proven framework and support for various computation fabrics, Cascading enables enterprises to leverage existing skill-sets, investments and systems to deliver on the promise of Big Data.
We continue to set the industry standard for building data applications,” said Chris Wensel, founder and CTO, Concurrent, Inc. “Bringing the power of Elasticsearch for fast, distributed, data search and analytics together with Cascading reflects our common goal – faster time to value in the deployment of data-centric applications. This is a feature our customers have been asking for, and we expect tremendous response from the community.”
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