AWS Certified Data Engineer – AssociateData Ingestion and TransformationEasy
A large manufacturing company needs to ingest real-time operational data from hundreds of industrial sensors located on its factory floor. The data includes temperature, pressure, and machine status, and must be processed immediately to detect anomalies and trigger alerts. The solution needs to handle fluctuating data volumes, ensure high durability, and integrate seamlessly with AWS Lambda for real-time processing. Which AWS service is most appropriate for ingesting this data?
- AAWS DataSync
- BAmazon Kinesis Data Streams
- CAmazon Kinesis Data Firehose
- DAmazon SQS
Show answer & explanationAnswer & explanation
Correct answer: B. Amazon Kinesis Data Streams
Amazon Kinesis Data Streams is designed for real-time ingestion of streaming data at scale, providing high throughput, durability, and direct integration with AWS Lambda for immediate processing. Its shard-based architecture allows it to handle fluctuating data volumes efficiently.
Why the other options are wrong
- A. AWS DataSync is used for transferring large amounts of data between on-premises storage and AWS, not for real-time streaming ingestion.
- C. Amazon Kinesis Data Firehose is primarily for delivering streaming data to destinations like S3 or Redshift, not for real-time processing with Lambda as the primary consumer.
- D. Amazon SQS is a message queuing service, not optimized for high-volume real-time streaming data ingestion.
Amazon Kinesis Data Streams
A real-time data streaming service capable of ingesting and storing large amounts of data from various sources.
- Provides high throughput and low latency for data ingestion.
- Data is stored for up to 365 days (default 24 hours).
- Integrates with AWS Lambda, Kinesis Data Analytics, and Kinesis Data Firehose.
Memory trick: Kinesis Streams: the real-time river for your sensor data.