Amazon Kinesis Data Streams lets you ingest streaming data (like IoT, app logs, clickstreams) in real time. You can write applications with Kinesis Client Library or use managed integrations to process the data with AWS Lambda or Kinesis Data Analytics. It’s built for high-throughput, low-latency processing.

Amazon Redshift is a fully managed, petabyte-scale data warehouse. It’s optimized for OLAP (analytical) queries. You load structured data from sources like S3, RDS, or DynamoDB, then run complex SQL queries quickly using columnar storage, massively parallel processing (MPP), and result caching.

AWS Glue is a serverless ETL service. You use it to:

• Crawl data sources to build a centralized catalog (metadata store).
• Write transformation jobs in Python (PySpark) or Scala.
• Schedule and orchestrate jobs without managing infrastructure.
• It’s integrated with S3, Redshift, and many other AWS services.

Amazon Kinesis Data Firehose is a fully managed way to capture, transform, and deliver streaming data to targets like S3, Redshift, OpenSearch, or Splunk. You don’t write custom consumers or worry about scaling; Firehose handles batching, compression, encryption, and automatic delivery.

• Standard for frequently accessed data.
• Standard-IA (Infrequent Access) or One Zone-IA for less-accessed data.
• Glacier / Glacier Deep Archive for long-term archival.

AWS Lake Formation simplifies creating secure data lakes on top of S3. It lets you:

• Ingest and organize data.
• Define fine-grained access controls at the table, column, or row level.
• Enforce consistent governance and auditing across analytics services (Athena, Redshift Spectrum, EMR).