Tray.io Announces New Capabilities To Democratize Orchestration, Integration, And Automation Of Real-time Event Streams

Tray.io Announces New Capabilities To Democratize Orchestration_ Integration_ And Automation Of Real-time Event Streams

Tray.io, the leader in low-code general workflow automation, today announced expanded event-streaming support for the Tray.io General Automation Platform with the addition of Publish/Subscribe (Pub/Sub), Queue Trigger, Queue Connector, and new connectors for message queues services and event streams.

The latest enhancements provide builders with more control over real-time data flows, making it easy for anyone to integrate, automate, and orchestrate real-time data and event streams across any applications, infrastructure, and devices.

Leveraging Tray.io’s new event-streaming capabilities, organizations can now drive greater value from real-time, event-based data at scale – without having to manage or learn complex infrastructure. 

Event streaming and event-driven architectures (EDA) are becoming an essential requirement for integration, automation, and analytics, and organizations everywhere are experiencing massive growth in real-time data.

According to IDC, nearly 30% of all global information will be real-time data by 2025. Until now, however, tapping into this data has been incredibly challenging, requiring specialized technical skills and complex code, infrastructure, and maintenance.

Gartner predicts that “by 2022, support of event notifications in low-code application platforms and API management tools will make EDA common in new application design.” (Gartner, Maturity Model for Event Driven Architecture, Yefim Natis, et al, Refreshed 30 November 2020, Published 28 June 2019)

“Digitization is driving organizations to integrate, automate, and analyze real-time data and event streams as their next source of competitive advantage,” said Rich Waldron, CEO and co-founder of Tray.io. “Up until now, doing so has required a heavy reliance on technical experts and code to manage the complexity of the underlying infrastructure, which can significantly throttle digital initiatives. By expanding the event-streaming capabilities of our low-code, serverless platform, we’re democratizing how business users, technologists, and developers can build and collaborate to turn real-time event streaming into powerful business value.”

New Pub/Sub Capability Provides Complete Control Over Orchestrating Real-time Streams

The Tray Platform’s Pub/Sub capability enables business users, technologists, and developers to maximize real-time flows by turning an event stream into multiple streams that can seamlessly feed into any number of workflows.

Builders can maximize the value of incoming events from webhooks, messages, or any other source by publishing them to any subscribing Tray Platform workflow. Builders can also establish topics and subscribers to workflows and turn a single event stream into a multi-stream powerhouse that can drive downstream app integration, data integration, and analytics workflows. 

Also Read: Server Market Revenue in India Crashes by 11.2% in 4Q20

Queue Trigger and Queue Connector Enable Message Queue Intelligence

API integrations can be orchestrated using the Tray Platform’s newly expanded queuing functionality to maximize integrity and build real-time applications, infrastructure, and device integrations. With the Tray Platform’s Queue Trigger and Queue Connector, builders have greater control over real-time data flows. Queue Triggers enable builders to instantly launch and immediately ingest event-stream data from queues such as Amazon SQS.

The Queue Connector allows builders to seamlessly flow data into internal queues to provide complete control over data flow management, API integration orchestration, and event-stream sequencing.

The platform already provides native connectors that enable low-code integration with message queues beyond Amazon SQS, including Apache Kafka, IBM MQ, and Rabbit MQ for use in any workflow. Tray.io’s built-in library of connectors lets builders easily connect event streams into their tech stacks, as well as create any application or data integration that routes real-time streaming data with low-code speed and simplicity.

Tray Platform Helpers can format any event-streaming data, or builders can optionally use scripts and tap into unlimited visual conditional logic to ensure complete control of data flows. 

Serverless Architecture for Elastic Scalability and Flexibility 

Workflow builders can take full advantage of the Tray Platform’s modern, serverless architecture to effortlessly manage streaming events at scale. The platform can elastically process practically unlimited data volumes without all the guesswork, painful sizing, and provisioning that comes with pre-serverless architectures.

The Tray Platform is able to add compute power on demand, dynamically adjusting compute as needed to process data, while providing complete control over asynchronous and parallel data processing.

Enabling Low-code Platform to Fuel Real-time Analytics 

Streaming analytics is one of the fastest growing analytics adoption areas. Flowing data into real-time analytics infrastructure just got easier, with event streaming that’s coupled with Tray Platform support for Apache Spark, AWS Kinesis, Microsoft Power BI, Databricks, and other services.

Unified with the Tray Platform’s already flexible visual business logic that provides low-code flexibility to dedupe, concatenate, aggregate, and cleanse data, analytics professionals can leverage the Tray Platform to accelerate any real-time analytics initiative. 

“Real-time, event-based data is the future of business growth,” continued Waldron. “By using low-code to democratize this data, any department in any organization can leverage it to realize value at the speed of business – without relying on development resources and complex infrastructure. Marketing departments can process product trial usage data in real time to personalize engagement and follow-ups to turn trial users into customers. Operations teams can automate real-time payment processing workflows and create real-time fraud detection workflows to provide additional security to their customers. Analytics professionals can easily move data from IoT platforms or other streaming sources into real-time analytics tools. The possibilities are truly endless.”

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