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AWS Serverless Match Your Data Stores to Business


Match Your Data Stores to the Business

The goal is to match the data storage to the business need and transaction type.

The key is to model your data repositories for transactional vs. query needs.

A transaction is a collection of statements that are executed one after another.

A query is a single request for data.

It is important to choose the data storage that suits your needs.

AWS serverless data storage is suitable for both transactional and query processing.


Match Your Data Stores to the Business Needs Video

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Data storage options

  • Amazon S3
  • Amazon DynamoDB
  • Amazon ElastiCache for Redis
  • Amazon Quantum Ledger Database
  • Amazon Aurora
  • Amazon RDS

Key features of Amazon S3

  • Data lakes
  • Economical states
  • Claim check design
  • Lambda data filtering (S3 Select)

Key features of Amazon DynamoDB

  • A millisecond key-value storage
  • Data changes made easy

Key features of Amazon ElastiCache for Redis

  • Suitable for real-time leaderboards
  • Low-latency in-memory data storage

Key features of Amazon Quantum Ledger Database (Amazon QLDB)

  • Distributed ledger
  • Model state transitions with cryptographic proof

Key features of Amazon Aurora

  • High-volume transactional data
  • Better performance and cheaper costs
  • Scales and shuts down based on traffic

Key features of Amazon Relational Database Service (Amazon RDS)

  • Runs familiar database engines
  • Less administration

Separate your data repositories into transactional and query needs.

You must handle execution failures that can happen with distributed data storage.


Related reads:

Databases on AWS

AWS Serverless Exercises

Test Yourself With Exercises

Exercise:

Which data store option is a millisecond key-value storage?

AWS 

Start the Exercise


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