Datawatch has increased the speed of real-time streaming and time series data analytics with stream processing engine Panopticon Streams. The engine can be used as a stand-alone solution or in conjunction with Panopticon’s Visual Analytics platform.
Peter Simpson, vice president of visualisation strategy at Datawatch Panopticon, says: “Capital markets customers will benefit from Panopticon Streams’ support of several key use cases, including best execution, real-time P&L, transaction cost analysis and trader and trading surveillance.
“The addition of the engine’s capabilities means we now offer a general purpose streaming analytics platform. It has applications anywhere organisations need to identify anomalies and outliers, investigate their causes, back test potential solutions, and then alter their business processes to address the issue. Given the software’s ability to handle real-time and time series data, we believe it will be most useful in electronic trading, telecommunications, energy, and IoT applications.”
The combination of stream processing, rapid data comprehension through visual analysis, faster investigation through time series analysis and playback down to the individual tick, is designed to help organisations make timely, more informed decisions that have immediate financial impact.
Built on the Apache Kafka platform, Panopticon’s solutions enable business users to build sophisticated Kafka data flows with no coding. Users who understand the business problems can create their own data flows, which can use information from a number of sources and incorporate joins, aggregations, conflations, calculations, unions and mergers, and alerts. Analysts can visualise processed data using Panopticon Visual Analytics and deliver it to Kafka, Kx kdb+, InfluxDb, or any SqL database.
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