Arcadia Adds Streaming Analytics Capabilities To Its Big Data Platform

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Big data analytics company Arcadia Data is shipping a new release of its business intelligence platform that adds streaming data visualization and analysis capabilities, a move that will provide businesses with real-time insights for Internet of Things applications.

The new release, Arcadia Enterprise 3.3, also provides native connectivity to Amazon S3 to enable visualization of data in the Amazon cloud storage system, providing a way to conduct SQL analysis on S3-stored data.

"We've seen pent-up demand from people with data in S3 who want to do more with it," said Priyank Patel, Arcadia's co-founder and chief product officer, in an interview with CRN.

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Arcadia, founded in 2012 and based in San Mateo, Calif., provides one of a new generation of business analytics tools designed to handle huge volumes of data, including data stored in Hadoop and in cloud-based systems.

The ability to apply visualization and analysis tools to streaming data is an increasingly important capability in the business intelligence arena and will become even more so as businesses deploy Internet of Things networks, sensors and devices and begin to collect and analyze IoT data.

Arcadia cites connected cars, manufacturing quality, cyber security and data center monitoring as some of the key IoT applications where streaming data analysis is in growing demand.

"Getting access to this data within seconds or minutes is critical to these use cases," Patel said.

Arcadia Enterprise can access streaming data in such systems as Apache HBase, Apache Kudu and, in the 3.3 release, Apache Solr, the open-source enterprise search platform. The new support for Amazon S3 comes in addition to existing support for Amazon Redshift, the AWS data warehouse service.

The enhancements in Arcadia Data 3.3 mean that the system can provide streaming data visualizations side by side with historical data reports within integrated data applications, according to the company, allowing users to switch back and forth between real-time and ad-hoc data discovery and reporting.

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