AWS Certification – Analytics Services – Cheat Sheet

Data Pipeline

  • orchestration service that helps define data-driven workflows to automate and schedule regular data movement and data processing activities
  • integrates with on-premises and cloud-based storage systems
  • allows scheduling, retry, and failure logic for the workflows

EMR

  • is a web service that utilizes a hosted Hadoop framework running on the web-scale infrastructure of EC2 and S3
  • launches all nodes for a given cluster in the same Availability Zone, which improves performance as it provides higher data access rate
  • seamlessly supports Reserved, On-Demand and Spot Instances
  • consists of Master Node for management and Slave nodes, which consists of Core nodes holding data and Task nodes for performing tasks only
  • is fault tolerant for slave node failures and continues job execution if a slave node goes down
  • does not automatically provision another node to take over failed slaves
  • supports Persistent and Transient cluster types
    • Persistent which continue to run
    • Transient which terminates once the job steps are completed
  • supports EMRFS which allows S3 to be used as a durable HA data storage

Kinesis

  • enables real-time processing of streaming data at massive scale
  • provides ordering of records, as well as the ability to read and/or replay records in the same order to multiple Kinesis applications
  • data is replicated across three data centers within a region and preserved for 24 hours, by default and can be extended to 7 days
  • streams can be scaled using multiple shards, based on the partition key, with each shard providing the capacity of 1MB/sec data input and 2MB/sec data output with 1000 PUT requests per second
  • Kinesis vs SQS
    • real-time processing of streaming big data vs reliable, highly scalable hosted queue for storing messages
    • ordered records, as well as the ability to read and/or replay records in the same order vs no guarantee on data ordering (with the standard queues before the FIFO queue feature was released)
    • data storage up to 24 hours, extended to 7 days vs up to 4 days, can be configured from 1 minute to 14 days but cleared if deleted by the consumer
    • supports multiple consumers vs single consumer at a time and requires multiple queues to deliver message to multiple consumers
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