Push Technology, a pioneer and leader in real-time data streaming and messaging solutions, is introducing new functionality for the company’s Diffusion Intelligent Event-Data Platform that consumes, enriches, and delivers data among applications, systems, and devices.
The new release expands the range of Diffusion’s unique Data Wrangling capabilities which provide developers with the tools to manipulate and transform event-data - in-flight - via topic trees, topic views, and time series with actual or custom time stamps.
The platform’s new functionality enables users to consume and mix disparate raw data sources and extract pertinent pieces of data to form new data streams for delivery of exactly and only the data required by recipients.
For development teams, Data Wrangling can be the most challenging and time-intensive aspect of application development because in-depth knowledge in this area is not often part of the in-house team’s expertise. The Diffusion platform unburdens development and helps speed applications to market.
Diffusion 6.6 introduces capabilities to augment event-data associated with a topic via topic view inserts. With topic view insert, users can now merge data from topics other than the selected source topic into JSON reference topics.
Diffusion 6.6 also introduces two major enhancements to time series topics. Users can now update a time series topic via the standard topic update API, treating a time series topic as if it were a single topic with the same event type as the time series.
This means that when updating time series topics,users can now use features like update constraints, update streams and the AddAndSet operation.
Diffusion 6.6 includes a new Python SDK to accommodate the growing adoption of Python by the developer community and market feedback.
Python is popular for general web development, scientific computing/data science, machine learning, and FinTech applications. The Python SDK supports subscribing to topics, and request-response messaging.
Diffusion’s Data Gateway makes it easy to consume both static and streaming data from a wide array of sources and provides capabilities to prepare the data for wrangling before an event-data is created and made ready for distribution.
Using the new Kafka Adapter, organizations can now efficiently and securely extend Kafka solutions over the Internet, streaming real-time data to millions of end-user applications. In addition, customers can easily manage the high-volume of data across geographically dispersed regions.
By supporting MQTT with Diffusion, software development teams can now bring state-of-the-art event-driven architecture to their IoT and Mobile solutions. The low code features of the Diffusion platform significantly reduces software development effort and the overall cost of deployed solutions.
Diffusion implements MQTT 5.0, the latest version of the specification. Both the TCP and WebSocket transports are supported, and connections can be secured using Transport Layer Security (TLS). Diffusion treats MQTT as a first-class protocol and acts as a session broker for MQTT clients in the same way as it does for Diffusion SDK clients.
For more information about these updates, visit www.pushtechnology.com.