Amazon DocumentDB Overview

We will talk about DocumentDB so we all know about Aurora RDS and Aurora RDS is AWS implementation of Postgresql or MySQL because it has the same API but it's built on AWS and it has some nice benefits to be cloud native.
DocumentDB is the same as Aurora RDS but for MongoDB (Which is NoSQL database).

- Mongodb is used to store, query and index JSON data so thanks to DocumentDB.
- Similar "deplyement concept" as Aurora RDS.
- Fully Managed, highly available with replication across 3 AZ.
- DocumentDB storage automatically grows in increments of 10GB.
- Automatically scales to workloads with millions of requests per seconds.

If using MongoDB on AWS so you pay for what you use in DocumentDB and there is no upfront cost but you need to understand the Architecture of DocumentDB, which is very similar to Aurora in order to understand its pricing.

DocumentDB - Pricing

- Pay as you Go, so pay for what you use. No up front cost.
- On-Demand Instances (pay per second with the minimum of 10 minutes)
- Database I/O: amount of IO used when Read/Write (per million IOs)
- Database Storage (per GB/month)
- Backup Storage (per GB/month)

We have database storage and then we have On Demand instances. We have primary instance and then replica instances that's up to you're going to pay for these on-demand instances, you can pay per second with the minimum of 10 minutes then these instances are going to do a read and write operations against your database storage so you're going to base for database IOs and this going to be counted per million IOs then of course the data is being stored on your database storage and therefore you're going to pay for the derby storage itself in gigabytes per month.

Amazon Timestream Overview

As name indicates, Amazon Timestream is a time series database so it's fully managed, fast, scalable, serverless time series database. Use cases for timestream would be to have an IoT application, operational applications, real-time Analytics or everything related to a Time series database.

- Automatically scale up/down to scale capacity.
- Store and analyse trillions of events per day.
- 1000s times faster & 1/10th the cost of relation databases.
- Schedule queries, multi-measure records and SQL Compatibility.
- Data storage tiering : Recent data kept in memory and historical data kept in a cost-optimised storage.
- Built-in time series analytics functions (helps you identify patterns in your data in real-time.
- Supports Encryption in-transit and at rest.

Amazon Timestream Architecture

Timeseries database can receive data from AWS IoT so internet of things, the Kineses Data Streams through them that can receive data as well, Prometheus, Telegraf, their integrations for that case the streams as well through conditions data analytics for Apache link can receive data into Amazon time stream and Amazon msk as well through the same process.

In terms of what can connect to do timesstream where can build a dashboards using Amazon Quicksight and machine learning using Amazon SageMaker, can connect to grafana or because there is a standard jdbc connection into your database and the application that is compatible with jdbc and SQL can leverage Amazon timestream.