Today, enterprises reap value from high velocity, real-time data such as device logs, sensor readings, social media feeds, and more. Real-time analysis of these streams requires a paradigm shift from batch-oriented architectures. New technologies such as Apache Kafka, Spark Streaming, Apache Storm, Apache Apex, and Amazon Kinesis have emerged to manage the velocity of big data.
While much of the discussion on real-time data focuses on machine processing, helping data users see these streams through real-time analytics and visualization is just as important. Zoomdata provides real-time visualization and streaming analytics based on self-service, interactive, subsecond response to ad hoc queries of high-velocity data. It’s purpose-built for streaming data, with an architecture that can push real-time updates from the source through our stream processing engine to end users via a WebSockets connection.
Zoomdata features out-of-the-box connectors to Twitter and Amazon Kinesis, as well as an interface for integrating with any stream processing infrastructure such as Kafka, Spark Streaming, Storm, and IBM Infosphere Streams. More than just simply monitoring these real-time data feeds, Zoomdata enables streaming analytics based on visual interaction with the stream. Users can dynamically filter the stream and change the aggregation level, as well as pause, rewind, and replay the stream.
Zoomdata enables users to execute streaming analytics against real-time, historical, and asynchronous data sources.