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by Until recently, the standard solution to capture, analyze, and store data in near real-time involved using the Hadoop toolset. This article explains how Snowflake has simplified the solution, and now supports high-performance real-time data capture, transformation, and processing using nothing more complex than industry-standard SQL. The requirements include the ability to capture, transform, and analyze data at a potentially massive velocity in near real-time.
The critical component that makes this possible is the Snowflake data warehouse which now includes a native Kafka connector in addition to Streams and Tasks to capture, transform, and analyze data in near real-time.
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