Amazon Web Services (AWS) is making available Amazon Kinesis Analytics, enabling continuous querying of streaming data using standard SQL. This allows developers to create SQL queries on live and continuous data for real-time analysis. No new programming skills are needed.
“AWS’s functionality across big data stores, data warehousing, distributed analytics, real-time streaming, machine learning, and business intelligence allows our customers to readily extract and deploy insights from the significant amount of data they’re storing in AWS,” said Roger Barga, General Manager, Amazon Kinesis. “With the addition of Amazon Kinesis Analytics, we’ve expanded what’s already the broadest portfolio of analytics services available and made it easy to use SQL to do analytics on real-time streaming data so that customers can deliver actionable insights to their business faster than ever before.”
Amazon Kinesis Analytics processes streaming data with less than 1-second processing latencies, enabling you to analyze and respond in real time. According to Amazon it provides built-in functions that are optimized for stream processing, like anomaly detection and top-K analysis, so that you can easily perform advanced analytics.
“You can now run continuous SQL queries against your streaming data, filtering, transforming, and summarizing the data as it arrives,” said AWS Chief Evangelist Jeff Barr. “You can focus on processing the data and extracting business value from it instead of wasting your time on infrastructure. You can build a powerful, end-to-end stream processing pipeline in 5 minutes without having to write anything more complex than a SQL query.”
“When I think of running a series of SQL queries against a database table, I generally think of the data as staying more or less static while the queries come and go pretty quickly,” Barr explained. “Rows are added, changed, and deleted all the time, but this does not generally matter when considering a single query that runs at a particular point in time. Running a Kinesis Analytics query against streaming data turns this model sideways. The queries are long-running and the data changes many times per second as new records, observations, or log entries arrive. Once you wrap your head around this, you will see that the query processing model is very easy to understand: You build persistent queries that process records as they arrive.”
AWS customers can employ Amazon Kinesis Analytics in minutes by going to the AWS Management Console and selecting a Kinesis Streams or Kinesis Firehose data stream. Amazon says that Kinesis Analytics takes care of everything required to continuously query streaming data, automatically scaling to match the volume and throughput rate of incoming data while delivering sub-second processing latencies.