AWS Database Services

Abstract

This article will explain the AWS Database service and its usage, typically AWS gives an easy option to set up, operate and scale on-demand basis. Most of the options are managed services, which eventually reduce manual operation cost.

Types of AWS Database Services

  1. Relation Database Services
  2. Aurora
  3. Elastic Cache
  4. Dynamo DB
  5. S3
  6. Athena
  7. RedShift
  8. AWS Glue
  9. Neptune
  10. Amazon OpenSearch

1. Relation Database Services (RDS)

  • This service is used for SQL, OLTP, Oracle systems
  • It has small operation downtime when a failure occurs.
  • Since its a managed service, the ownership borne by AWS
  • It multi-AZ feature with 5 scaling replicas, so the readability is good.
  • The performance of this service is based on EC2 and EBS provisioning.
  • It calculates the cost based on the hourly provision of EC and EBS.

2. Aurora

  • This service has a serverless facility with a multi-master option. So if one master fails, then the immediate node will work as a Master node
  • Aurora is managed service, the ownership will be taken care of by AWS.
  • It has auto-scaling storage, so less operation work required
  • This service has Multi-AZ and with high availability, possibly more than the RDS.
  • The cost comparison for this service may be lower than the Enterprise grade system.

3. Elastic Cache

  1. This behaviour of the service is similar to RDS however this is especially for the cache system.
  2. It has a Multi-AZ facility and is able to do Shading and Clustering option.
  3. The performance option of this service is good because of the im-memory facility.

4. Dynamo DB

  • This is a serverless managed service.
  • It can replace the elastic cache option.
  • We can use DAX to increase the performance with the help of applying the Cache method.
  • It can only query Primary Key and SortKey

5. S3

  • This is not an exact database, however, if we want to store instructed data like images, videos or any other raw file, then this is the right place to push as a first step. 
  • S3 is a fully managed service, so no need for any sort of provisioning is required
  • It has 99.999999999% durability and 99.99% availability with multi-AZ and Cross region replica options.
  • Also, it has an option as acceleration transfer, to move the data.
  • The cost to use these services is based on consumption, such as pay as you go option. 

6. Athena

  • Again this is not a conventional database system, however, this suppose to be used to query data, eg., Fetching data from S3.
  • It uses a presto engine, which is a high-end query engine. so we can yield results better fastened.
  • The cost to use this service is pay per query

7. RedShift

  • It acts like RDS
  • On top of that, this service has an option called auto-healing, a cross-region and a snapshot copy feature.
  • It does 10x performance than other data warehousing tools.
  • It has extendable facilities compared to Athena where we can opt to do joins, and aggregations and are also able to do fastened queries.

8. AWS Glue

  • Actually, this is not a conventional database system, however, this service is great to do ETL operations. 
  • This service is useful to prepare and transform data for analytics.
  • Typically with the help of Glue data catalogue and glue data crawler, we can get data from S3, RDS and Dynamo DB

9. Neptune

  • Its looks like RDS 
  • This service best suits Graph.
  • The cost calculates based on the pay-per-node provisioned. 
  • It has multi-AZ and clustering options.

10. Amazon Open Search

  • It's again similar to RDS
  • It is the successor of Elastic Search
  • In dynamo DB, we can find by using Primary and Index, however with the help of open search, we can find any fields, even if partially matches.
  • This services comes with open search dashboard( KIABANA)

I hope this article gives a high-level idea about AWS Database service. Thanks for reading this, Will meet in next article :)


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