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Imply Joins the Connect with Confluent Partner Program, Creating a Comprehensive Platform for Real-Time Analytics Applications

Imply Joins the Connect with Confluent Partner Program, Creating a Comprehensive Platform for Real-Time Analytics Applications

Imply, the company founded by the original creators of Apache Druid announced it has joined the Connect with Confluent partner program, an initiative designed to help organizations accelerate the development of real-time applications through native integrations with Confluent Cloud. This partnership brings together Imply and Confluent’s cloud-managed services for Druid and Apache Kafka, respectively, offering developers.

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“Data streaming is now a critical business requirement as companies shift toward a digital-first approach to everything”

  • Real-time analytics on streaming data of any scale: Stream millions of events per second from Confluent Cloud to Imply Polaris, the cloud database service for Druid, with subsecond latency—making data instantly available for real-time analytics.
  • A connector-free experience: Ingest data from Confluent Cloud directly into Polaris without installing and managing a connector.
  • Cloud-native, fully-managed real-time architecture: Build real-time applications on Kafka and Druid without the production risk and infrastructure management, while accelerating time to value for real-time analytics use cases.

Organizations now have a simplified experience for analyzing Kafka streams via Druid, the real-time analytics database built for streaming data, as Imply and Confluent together have made it easier to power mission-critical and customer-facing applications with real-time data. These applications are used in a wide range of industries for a variety of use cases, including security and fraud analytics, product analytics, IoT/telemetry analytics, and application observability.

“Imply’s partnership with Confluent is anchored in the transformative value of data in motion and in the commonality of delivering cloud-native services based on widely deployed open-source technologies,” said Praveen Rangnath, Chief Marketing Officer, Imply. “The seamless integration of Imply Polaris with Confluent Cloud empowers organizations to easily unlock the full potential of their streaming data with real-time analytics—thereby extending the value of their data-in-motion with analytics-in-motion.”

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“Confluent Cloud with Imply Polaris is rapidly becoming the architecture of choice for injecting analytics into real-time customer experiences and optimized business operations,” said John Broad, Vice President, Partners & Alliances, Imply. “By partnering with Confluent and its robust ecosystem of systems integrators and technology partners, we enhance the durability and agility of analytics solutions while bringing innovative features, like schema auto-discovery for streaming data, to our joint customers.”

Introducing the Connect with Confluent program

Connect with Confluent gives organizations direct access to Confluent Cloud, the cloud-native and complete data streaming platform that processes more than an exabyte of data per year. It’s now easier for organizations to stream data from anywhere to Druid with a fully managed Kafka service that spans hybrid, multi-cloud, and on-premises environments. In addition, the program supercharges partners’ go-to-market efforts with access to Confluent engineering, sales, and marketing resources. This helps ensure customer success at every stage from onboarding through technical support.

“Data streaming is now a critical business requirement as companies shift toward a digital-first approach to everything,” said Paul Mac Farland, Vice President, Partner and Innovation Ecosystem, Confluent. “However, many companies don’t have the resources needed to successfully bring a complete set of data streaming capabilities to their applications and end users. Connect with Confluent solves this problem, helping Confluent technology partners accelerate their customers’ data-driven ambitions so they can win in the modern digital era.”

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