SWIM.AI Launches DataFabric for Edge, Streaming Data in Azure

eWEEK PRODUCT NEWS ANALYSIS: Enterprises can collect, classify, reduce and analyze edge/streaming data to derive real-time insights in Microsoft Azure deployments.

SWIM.AI

As we start to wind down 2019 and look ahead to the new year and decade, three key trends will be leading the way into the future of IT: edge computing, data fabrics and composable infrastructures. All will gain more importance as IT systems get faster, more sophisticated and easier for line-of-business employees to use.

  • Basically, edge computing is any type of computing that doesn't take place in a data center. There's more to it than that, but that's where we start the definition.
  • A data fabric is an architecture and set of data services that provide consistent capabilities across a choice of endpoints spanning on-premises and multiple cloud environments. Data fabrics simplify and integrate data management across cloud and on-premises to accelerate digital transformation.
  • Composable infrastructure is a trendy infrastructure architecture that was spurred by HPE's entry into the genre a few years ago. It is designed to ensure that the exact amount of computing resources—from processing power and storage to network fabric and virtualization—can be rapidly pulled together from a single resource pool to support an application, and then returned to the pool when they're no longer needed for the workload. It’s a just-in-time approach that enables optimization of resources at all times.

With all this in mind, San Jose, Calif.-based SWIM.AI, creator of the Swim open-source distributed application/data platform, has announced general availability of its new enterprise software product, Swim DataFabric. DataFabric is fully integrated with Microsoft Azure services and can be quickly deployed and managed using the Microsoft Azure IoT suite.

Edge and streaming data can now be economically collected and analyzed in real time with insights and labeled data delivered to Azure Data Lake Storage for use by enterprise applications that use Azure PowerBI or are built with Azure Power Apps.

'Analyze, Act and Then Store,' Not 'Store and Then Analyze'

DataFabric enables collection, labeling and local analysis of data, as it is generated, delivering immediate insights and analysis, SWIM.AI said. Critical insights are immediately acted upon, and the most important data identified, enabling real-time visualization, efficient data labeling and delivery. Insights and underlying data are then delivered to a real-time API to the Azure Data Lake or for use by existing applications.

“SWIM.AI provides a unique product for edge/streaming data—software, which is lightweight, able to run anywhere—at the edge or in the cloud—enabling local data collection, reduction, analytics and delivers both data and insights to the Microsoft Azure Cloud in real-time,” CEO Ramana Jonnala said in a media advisory. “For the enormous volume of real-time/edge data being created by devices, sensors, machines and people the only economic way to handle the data is locally and in real-time.”

Intelligent 'On-Ramp' to Azure for Edge/Streaming Data

Swim DataFabric provides a lot of functions. It collects, cleans, labels and analyzes edge/streaming data to enable enterprises to integrate insights in Azure applications (an “intelligent dataflow pipeline”).

DataFabric can be deployed and managed using Azure IoT and provides a sort of “data on-ramp” to Azure services such as Power BI, PowerApps, Azure Event Hub and ADLS Gen 2. Swim DataFabric collects edge/streaming data and automatically builds digital-twin models of each real-world data source and analyzes their relationships, using real-world context such as location, proximity or correlation.

DataFabric digital twin models create a stateful, distributed data map for real-time processing, analytics, learning and prediction, providing a streaming framework and full integration with Azure cloud services. The platform takes advantage of the Microsoft Azure reference architectures for IoT to enable easy deployment and lifecycle management.

DataFabric also supports:

  • Full integration with Azure Event Hub and efficient delivery of edge/real-time data to Azure PowerBI;
  • Edge/real-time data is collected, reduced, labeled, analyzed and delivered to:
    • Azure Data Lake Storage using the Common Data Model;
    • Azure services including: Event Hubs and Azure Data Services for real-time visualization, creation of new applications and deeper analysis
  • DataFabric integrates seamlessly with Azure IoT Hub and DPS for automatic device management and deployment of software to the edge and Azure;
  • Azure users can combine corporate data sets with real-time data using DataFabric;
  • DataFabric software is able to run locally in Azure IoT Edge or in the Microsoft Azure Cloud.

Significant Reduction in Infrastructure Costs

By collecting and analyzing data with Swim DataFabric, businesses benefit from real-time visibility of all data generating assets (< 1 sec) and reduction in costs from data storage, processing and databases licenses (up to 75%). Swim DataFabric software is highly efficient, lightweight (<2MB) and able to run anywhere (small compute devices, data centers or clouds) and works with existing software, systems and applications.

SWIM.AI works with systems integrators, OEMs and cloud vendors to provide custom solutions.

Swim Product Information

  • SWIM Platform: Open-source distributed data platform for developers, using stateful Web Agents and streaming APIs to create real-time models of distributed systems from edge/streaming data
  • SWIM DataFabric: Edge/streaming data solutions for businesses delivering visibility and insights in real time. Fully integrated with Microsoft Azure, Azure IoT and Azure Services

Swim DataFabric is available through license pricing based on devices or data volumes, the company said.

Chris Preimesberger

Chris J. Preimesberger

Chris J. Preimesberger is Editor-in-Chief of eWEEK and responsible for all the publication's coverage. In his 15 years and more than 4,000 articles at eWEEK, he has distinguished himself in reporting...