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ThatDot, a Portland, Oregon-based startup that offers a complex event processing (CEP) platform to capture the full value of streaming data for advanced AI and ML applications, has released open source software source to help developers and data pipeline engineers create high-volume, real-time event processing workflows at scale.

Officially dubbed Quine, the solution combines event streaming and graph data technologies to connect to existing data streams and create data in a stateful graph. Then, it parses this graph for user-specified “sticky queries” and streams the results to trigger real-time event-driven workflows.

Quine speeds up processing

The offering comes as the answer to event processing frameworks such as Flink. Ryan Wright, the co-founder of THATDot, notes that these previous-generation solutions have various limitations and spend a tremendous amount of time – on the scale of months – and effort to create complex event-driven architectures that only work on short windows of data time in memory. and miss the big picture.

Quine, on the other hand, uses a handful of queries to turn the tedious process of data engineering into an afternoon job. It can eliminate batch processing, multilevel joins, and other time-consuming and obsolete processes that slow down and stall continuous data analysis. This way, data pipeline engineering teams can easily interpret high-volume event data streams, innovate and ship products faster, and use emerging Graph AI tools to drive the next wave. machine learning.

The company, along with its early access launch partners and community members, has also created pre-built app functions called “recipes” to help data pipeline engineers with several event stream use cases. . This includes real-time propagation of Blockchain beacons to track money laundering, CDN cache efficiency analytics to continuously monitor CDN logs to materialize cache efficiency and generate alerts, and Kubernetes Event Observability to ingest Kubernetes events and calculate status by component, pod, and service for alerts. and traces of root causes.

Previous request

ThatDot created the Quine streaming graphics solution in 2014 and has been using it as part of its software portfolio ever since. In 2015, Wright had also led a team of researchers and developers on the DARPA Transparent Computing program and used Quine to create new capabilities for finding and stopping advanced persistent threats (APTs). Today, the company brings it to data pipeline engineers around the world.

“The decision to open the Quine Streaming Chart underscores THATDot’s belief that the best infrastructure software thrives within an open and diverse community of contributors, and that well-designed, freely available software benefits everyone,” notes the company on Quine’s website. The solution is also accessible on GitHub.

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