thatDot Streaming Graph can process multiple data streams simultaneously, combining them into a single graph for analysis. It can integrate as both a source and a sink for Apache Kafka, Kinesis, SQS pipelines, and other data streams.
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Graph-Based Data Analysis
The product uses graph analysis techniques to process streaming data, allowing for deep analysis of relationships between data points. It can perform analysis on IP addresses, people, and other entities directly without converting categorical data into numerical data.
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Real-Time Pattern Detection
thatDot Streaming Graph uses standing queries to continuously monitor for specified patterns in the data stream. When a pattern is complete, it delivers key insights within milliseconds, highlighting critical information.
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Time-Unrestricted Querying
The product allows querying across time without being restricted to specific time windows. It can find patterns, anomalies, and problems by querying the entire historical and current data in real-time.
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High-Speed Data Processing
thatDot Streaming Graph offers parallelized distributed compute capabilities, allowing it to read and write data at high speeds and handle out-of-order data. It has been tested to achieve throughput of over 1 million events per second.
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