Introduction to Amazon Kinesis Service

Amazon Kinesis ingests, buffers, and processes real-time streaming data. This allows you to gain insights in seconds or minutes rather than hours or days.

Amazon Kinesis is a tended, scalable, cloud-based service. This service enables the real-time processing of large amounts of data per second. It is intended for real-time applications. Developers can collect data from multiple sources while scaling up and down to run on EC2 instances.

Kinesis captures, stores, and processes data from large, distributed streams such as event logs and social media feeds. After processing the data, Kinesis distributes the data to multiple consumers simultaneously.

But, before moving forward, let’s go through the topics that we will be covering in this blog:

1. Core services of Kinesis
2. Features of Kinesis
3. Limitations of Kinesis
4. Use cases of Kinesis
5. Why use Kinesis?

Core services of Amazon Kinesis

Kinesis is an AWS platform for sending streaming data. It simplifies the analysis of streaming data and allows you to create custom applications based on your business requirements. Amazon Kinesis provides three core services. These three services are:

1. Streams
2. Firehose
3. Analytics

Kinesis Streams

Amazon Kinesis Data Streams enables large-scale data ingestion and real-time streaming data processing. It allows you to order records as well as read and replay them in the same order.

Shards make up Kinesis streams. For reads, shards provide five transactions per second. The number of shards you specify for it determines the data capacity of your stream. The total capacity of the Amazon Kinesis stream is the sum of all shard capacities.

Kinesis Firehouse

In a nutshell, the Amazon Kinesis Data Firehouse service is an extract, transform, and load (ETL) service. This service reliably catches, converts, and provides streaming data to data lakes, stores, and analytics services. To create a delivery stream with Firehouse, you can select your destination and start streaming real-time data with just a few clicks.

Kinesis Firehose also delivers streaming data to Amazon S3, Amazon Redshift, and Amazon Elasticsearch. You do not have to manage the resources with Kinesis Firehouse.

Kinesis Analytics

Amazon Kinesis Data Analytics allows you to quickly write SQL code that reads, processes, and stores data in real-time. Analytics is the simplest way to transform and analyze real-time streaming data using Apache Flink.

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Analytics enables you to run SQL Queries on the data contained in the kinesis firehose. You can use SQL Queries to store data in an S3, Redshift, or Elasticsearch cluster. Essentially, data is analyzed within Kinesis using SQL-like query language.

Features of Amazon Kinesis

There are many features of Amazon Kinesis. Some of those features are:

Integration: kinesis can integrate with other Amazon services such as Amazon Redshift, Amazon S3, and Amazon DynamoDB.

Cost-effectively: Kinesis is a low-cost solution for workloads of any size. You can use the Pay as you go model for the resources you will use. You can also pay hourly for the throughput that you need.

Fully managed: Amazon Kinesis is fully executed. It also keeps running your streaming applications without the need for you to manage any infrastructure.

Real-time processing: This feature enables us to collect and analyze information in real-time, such as stock trade prices, rather than having to wait for a data-out report.

Create kinesis applications: Amazon Kinesis provides developers with client libraries to create and run real-time data processing applications. When you include the Amazon Kinesis Client Library in your Java application, it will notify you when new data is available.

Simple to use: Using Amazon Kinesis, we can quickly create a new stream, set its requirements, and begin streaming data.

Scalable: With very low latencies, Kinesis can handle any amount of streaming data and process data from hundreds of thousands of sources.

Limitations of Amazon Kinesis

Some of the limitations of Kinesis are:

1. You can have unlimited streams in your account when using the provisioned mode.
2. A data blob in a single record can only be 1 megabyte in size (MB).
3. Up to five read transactions per second can be supported by each shard. Each read transaction can provide up to 10,000 records, with a maximum transaction size of 10 MB.
4. Within 24 hours, you can switch between on-demand and provisioned capacity modes for each data stream in your AWS account.
5. With the on-demand capacity mode, you can create up to 50 data streams within your AWS account by default. Contact AWS support if you need this quota increased.

Use cases of Amazon Kinesis

Some of the use cases of Kinesis are:

1. Analyzing real-time stock data
2. Social media monitoring in real-time
3. Tracking and availability of shared assets
4. Detecting anomalies in IoT device readings
5. Data-driven real-time digital advertising updates

Why use Amazon Kinesis?

Kinesis has some distinct advantages as a streaming tool. It is, in particular, a managed service, which means that AWS handles much of the system administrator rather than developers. Because of this, developers can concentrate on their code rather than system management.

Conclusion

If you want to learn more about AWS services you can refer to the following blogs:

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