1. Timestream overview
In this section, let’s talk about Time Stream. A new database service from AWS. Time stream is a fully managed, fast and scalable server less time series database service. So what exactly is time series? Time series data measures how things change over time. So an example of Time series data is temperature data or weather data that you typically see in weather forecast. So you can capture data coming in from different sensors or different IoT devices and store it in your database in a time ordered fashion. So that’s where Time Stream comes into play. So you can use Time Stream to store and analyze trillions of time ordered events per day.
And it offers 1000 times faster query performance at one 10th of the cost of typical relational databases. And it also automates the roll ups, retention, turing, and compression of data. So here are some of the use cases of the Time Stream database. You can use it to store log data for DevOps. You can use it to store the sensor data coming in from different IoT devices for use with your IoT applications. You can use it to store clickstream data for web traffic monitoring. You can also use it to store the industrial telemetry data that you can use for equipment maintenance. And use cases are numerous. Now, let’s see what Time series data looks like.
Time series data is simply a series of data points ordered in time. So here you are seeing a graph of hourly temperature data. So that’s an example of a typical time series data. All right, time Stream is a serverless offering, which means you don’t have to provision any servers. It can automatically scale, writes, storage, and query capacity on demand. You can set the data retention policies for each table. The data is, of course, organized by time intervals. And the Time Series database uses a time series specific data compression, which results in less scanning and faster performance. You have separate data processing layer for data ingestion, for storage sharing, and for queries.
And Time Stream uses an adaptive query engine that adapts to different time series data sets. And on top of this, it also offers built in analytics like interpolation smoothing and approximation. And you can definitely use relational databases or even DynamoDB for storing your time series data. But relational databases are generally not a good fit for Time series data sets. And if we talk about DynamoDB, you can definitely use it to store your Time series data. But Time Series Database has been purpose built to store time series data sets, and it does provide many additional features and functionalities like advanced analytics capabilities, which are not available if you store Time series data in DynamoDB.
So you don’t have to reinvent the wheel when you use Time Stream instead of other database solutions. Right, let’s look at the Time Stream use cases. So you have Time series data coming in from different sources, and you collect it into Time Stream database, or you store it into your time stream database. Then you can use it for business analytics, you can use it for machine learning, or you can use it for custom applications that use your time series data sets. So these are some of the use cases for time stream database. Let’s continue to the next lecture.
2. Timestream pricing
Now, let’s look at Timestream pricing. Now, Timestream is a serverless database. You don’t have to provision any servers, so you pay only for what you use. So you pay for the number of writes. These are priced on a per million rights basis. And the reads or the query operations are priced on per TB of data that that gets scanned by your queries. And on top of this, you also pay for the storage per GB, so you can use in memory SSD or magnetic storage. And just like any other AWS service, you would pay the standard data transfer charges as well.
So that’s all about the Time Stream database. And as of recording this video, Time Stream is still in preview. So this is all we know about it right now. And we still don’t have access to the Time Stream console. And from the examination perspective as well, I believe this is all you need to know about Time Stream as of now. With that, we come to the end of this section. Let’s continue to the next next one.
