AWS Certified Solutions Architect – ProfessionalContinuously Improve Existing SolutionsMedium
A startup is building a new real-time analytics platform. Their existing data ingestion pipeline uses Amazon Kinesis Data Streams. They need to perform continuous, low-latency processing of streaming data to derive insights within seconds, such as anomaly detection and real-time dashboards. Which AWS service should they use to efficiently process this streaming data?
- AAmazon Kinesis Data Firehose
- BAmazon Kinesis Data Analytics for Apache Flink
- CAWS Glue
- DAmazon EMR with Apache Spark
Show answer & explanationAnswer & explanation
Correct answer: B. Amazon Kinesis Data Analytics for Apache Flink
Amazon Kinesis Data Analytics for Apache Flink is a fully managed service that allows for real-time processing of streaming data with low latency. It's ideal for use cases like anomaly detection and real-time dashboards directly from Kinesis Data Streams, providing powerful analytical capabilities without managing underlying infrastructure.
Why the other options are wrong
- A. Amazon Kinesis Data Firehose is for delivering streaming data to destinations like S3, Redshift, or Splunk, not for performing continuous analytical processing on the stream itself.
- C. AWS Glue is an ETL service primarily for batch processing and data cataloging, not for continuous, low-latency real-time stream processing.
- D. Amazon EMR with Apache Spark can process streaming data, but it requires managing an EMR cluster and is often more suited for larger-scale, complex batch or near-real-time processing, potentially introducing more latency than Flink.
Kinesis Data Analytics for Apache Flink
A fully managed service for processing streaming data in real time with Apache Flink, enabling powerful analytics with low latency.
- Processes data from Kinesis Data Streams or Firehose.
- Supports SQL, Java, Scala, and Python for stream processing.
- Ideal for real-time dashboards, anomaly detection, and machine learning.
Memory trick: Flink is the lightning-fast river current, processing data as it flows.