AWS S3 Vs. DynamoDB Vs. RDS Aurora Vs. Redshift

In this video, we will describe the differences between AWS S3, RDS Aurora, Redshift, and DynamoDB.

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Amazon S3:
Amazon Simple Storage Service (Amazon S3) is a storage service that allows enterprises/individuals to store and protect any amount of data.
Amazon S3 is extremely easy to use and allows enterprises to organize their data and configure finely-tuned access controls.
Amazon S3 extremely durable to 99.999999999% (11 9’s).

RDS Aurora:
Amazon Aurora is a fully managed by Amazon Relational Database (RDS) service.
Amazon Aurora is a MySQL and PostgreSQL-compatible relational database.
You do not have to deal with administration tasks such as hardware provisioning, creating backups and database setup. It features continuous backup to Amazon S3, and replication across three Availability Zones.

RedShift:
Amazon Redshift is the fastest cloud data warehousing service that could be used to perform business analytics.
Extremely fast and optimized performance since it relies on columnar storage and data compression.
Queries are run against data stored in redshift storage or against data stored in S3.
Redshift uses a unique data warehousing architecture that relies on Massively Parallel Processing (MPP). MPP parallelize and distribute SQL operations. Redshift uses machine learning to optimize performance.

Amazon DynamoDB:
Amazon DynamoDB is a fully managed NoSQL key-value and document database (not relational database so no schema is required).
DynamoDB is extremely scalable with minimum latency.
Create a new table for your application and let DynamoDB handle the rest.

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#dynamodb #aurora #redshift #s3

Видео AWS S3 Vs. DynamoDB Vs. RDS Aurora Vs. Redshift канала Prof. Ryan Ahmed