Amazon Timestream: Overview, Limitations, Pricing & Many More

Amazon Timestream is a time series database service for IoT and operational applications that is fast, scalable, and serverless. It enables the storage and analysis of trillions of events per day up to 1,000 times faster and at a fraction of the cost of relational databases.

In this blog, we will discuss Amazon Timestream:

• Overview
  
• How was Timestream built?
  
• Timestamp
• Characteristics
• Limitations
• Benefits
• Use Cases
• Pricing
• FAQ’S
  

What is AWS Timestream?

By keeping recent data in memory and moving historical data to a cost-optimized storage tier based on user-defined policies, Amazon Timestream saves you time and money when managing the lifecycle of time series data. The purpose-built query engine in Amazon Timestream allows you to access and analyze both recent and historical data without specifying whether the data is in-memory or cost-optimized.

It includes time series analytics functions that allow you to identify trends and patterns in your data in real-time. It is serverless and scales up and down automatically to adjust capacity and performance.

How was Timestream built?

• Timestream began by decoupling data ingestion, storage, and query so that they could all scale independently.
• The design keeps each sub-system simple, making it easier to achieve unwavering reliability. It also eliminates scaling bottlenecks and reduces the chances of correlated system failures, which become more important as the system grows.
• To manage overall growth, the system is cell-based – rather than scaling the system as a whole, we segment the system into multiple smaller copies of itself (called “cells”) so that these cells can be tested at full scale, and a system problem in one cell cannot affect activity in any of the other cells.
• The cell-based architecture is similar to the approach we took in Amazon Aurora, and it has served us well in recent years in maintaining industry-leading service availability.

A timestamp is a computer’s record of the current time of an event. The timestamp is used for values that contain both time and date components.

The timestamp is a common feature in analog cameras. However, people are increasingly turning to DSLRs and smartphones, resulting in a significant decline in the use of analog cameras.

CheckSum, time-t, CRLF, time, and local time are some of the names for timestamps.

A digital timestamp traces a PDF signature with the time and date as proof of authenticity.

Characteristics of Amazon Timestream-

The characteristics of the time stream are as follows:

1. Because you cannot delete or update data in the Timestream, all data sent to it is an append-only table. The data is not deleted until the retention period expires.

2. A Timestamp, one or more dimensions, a measurement name, and a value are all required for all records.

3. Records are not editable or deletable. Records are only removed when their retention limit within the magnetic tier is exceeded (infinite storage is an option).

4. Multiple measures can be represented logically as multiple individual records (one step per record).

5. Scales automatically to handle real-time data ingestion at high speeds.

Limitations of Amazon Timestream-

There are three main points that you should consider before using Timestream for any production workloads.

1. Currently, only the US-east-1, US-east-2, US-west-2, and EU-west-1 regions are covered by the service.
2. It supports ANSI-2003 SQL, but it does not support cross-table joins. You could use joins between CTEs that are based on the same table, but the tables are isolated from each other and thus cannot be joined across.
3. Unlike relational databases, the tables in Timestream are append-only, which means that no deletes or updates are permitted.

Benefits of Timestream-

1. High performance at low cost– It is intended to enable interactive and affordable real-time analytics, with query performance that is up to 1,000 times faster and costs as little as one-tenth the price of relational databases.
2. Serverless with auto-scaling- It is serverless, which means there are no servers to manage or capacity to provision, allowing you to focus on developing your applications.
3. Data lifecycle management- It simplifies the complex process of managing data throughout its lifecycle. Storage tiering is available, with a memory store for recent data and a magnetic store for historical data.
4. Simplified data access- You no longer need to utilize many tools to access recent and previous data thanks to Amazon Timestream.
5. Purpose-built for time series- SQL has built-in time series functions for smoothing, approximation, and interpolation that make it easy to swiftly evaluate time series data.
6. Always Encrypted- For the purpose of encrypting data in the magnetic store, Amazon Timestream additionally lets you provide an AWS KMS customer-managed key (CMK).

Use cases of Amazon Timestream-

1. IoT applications- Using built-in analytical tools like smoothing, approximation, and interpolation, Amazon Timestream enables you to easily evaluate time series data produced by IoT applications.

2. DevOps applications- DevOps systems that track usage and health metrics and analyze data in real-time to boost performance and availability are best suited for Amazon Timestream.

3. Analytics applications- The incoming and outgoing web traffic for your apps can be stored and processed using Amazon Timestream when you have clickstream data. Additionally, it offers aggregate capabilities to examine this data and gain insights into things like path-to-purchase and cart abandonment rates.

Pricing of Amazon Timestream

With Amazon Timestream you only pay for what you use, there are no up-front costs, and there is no minimum fee.

At the time of writing, the pricing is based on:

• the quantity of data that is temporarily kept in memory, expressed in GB per HOUR.
• the volume of data kept in a magnetic or SSD storage device for long-term storage, expressed in GB each month.
• queries per GB scanned
• writes are counted in millions of 1 KB data piece writes.
• cross-region data transfer (if applicable)

Frequently Asked Questions:

Q1. What is the advantage of Amazon Timestream over other databases?
Ans- The Amazon Timestream database outperforms relational databases thousands of times and costs a fraction of the price. Furthermore, it enables you to analyze and store trillions of events every day.

Q2. Where is the Amazon Timestream database used?
Ans- The Amazon Timestream database’s most common use cases are IoT, DevOps, Analytics, and faster query output applications.

Q3. What performance can I expect from Amazon Timestream?
Ans- It provides near-real-time data ingestion latencies. You can run queries that analyze tens of gigabytes of time-series data from the memory store in milliseconds and analytical queries that analyze terabytes of time-series data from the magnetic store in seconds.

Q4. How can I send data to Amazon Timestream?
Ans- From linked devices, IT systems, and industrial machinery, you may gather time series data and write it into Amazon Timestream. Utilizing data collecting tools like AWS IoT Core, Amazon Kinesis Data Analytics for Apache Flink, Telegraf, or the AWS SDKs, you can submit data to Amazon Timestream.

Q5. What are the benefits of the memory store?
Ans- The memory store is a write-optimized store that receives and deduplicates time series data. Additionally, it accepts and handles data that arrives late from systems and programs with intermittent connectivity. For point-in-time queries that need low latency, the memory storage is additionally optimized.

Q6. What visualization, analytics, and machine learning (ML) tools can I use with Amazon Timestream?
Ans- Utilizing Amazon QuickSight and Grafana, you can visualize and examine time-series data in Amazon Timestream. You can also use Amazon SageMaker with Amazon Timestream for your ML requirements.

Q7. Does Amazon Timestream support data encryption?
Ans- Data is always secured in Amazon Timestream, whether at rest or in transit. You can also specify an AWS KMS customer-managed key (CMK) with Amazon Timestream to encrypt data in the magnetic store.

Q8. Can I use Amazon Timestream in an Amazon Virtual Private Cloud (VPC)?
Ans- Using VPC endpoints, you can connect to Amazon Timestream from your Amazon VPC. Without the need for an internet gateway or a Network Address Translation (NAT) instance, Amazon VPC endpoints offer dependable connectivity to the Amazon Timestream API.

Q9.What is a quorum?
Ans- The NoSQL technique known as a quorum (read nodes + write nodes > a total number of nodes) is used to ensure consistency in data.

Related Links/References

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