Amazon Kinesis is a service provided by Amazon Web Service that allows users to process a large amount of data (which can be audio, video, application logs, website clickstreams, and IoT telemetry )per second in real time. In today’s scenario handling a large amount of data becomes very important and for that, there is a complete whole subject known as Big Data which works upoon how to process or handle the streams of large amounts of data. So Amazon came up with a solution known as Amazon Kinesis which is fully managed and automated and can handle the real-time large streams of data with ease. It allows users to collect, store, capture, and process many logs from distributed streams such as social media feeds. It makes users focus on the development by taking any amount of data from any source to process it. After processing all the data, Kinesis also distributes all the data to the consumers simultaneously.
Amazon Kinesis
Amazon kinesis is used to analyze streaming data and process it for further use at large amounts of scales. It is fully managed by Amazon itself so it is easy to easy to capture, process, and store streaming data in the cloud. It is very useful for the developers to build an application by which they can continuously ingest process and analyze data streams from various sources as mentioned below.
- Application and service logs.
- Clickstream data.
- Sensor data.
- In-app user events.
How Amazon Kinesis Works?
Amazon Kinesis working can be divided into four stages as follows.
1. Data Ingestion
Amazon kinesis will collect the data or receives the data from the different data streams like application, sensors, and so on. The data that is going to be received from the different sources can be in different formats like JSON and Binary. It can also accept the data of real-time applications.
2. Sharding and Scaling
The smaller parts of the data called the shards the data which is received from the different sources are divided into smaller shards for redundancy and fault tolerance. There are no limits for the shards amazon kinesis can scale the shards horizontally depending on the requirement.
3. Processing and buffering
After sharded the data will be prepared for further use like it will apply filtering or record aggregation before storing it.
4. Making the data accessible
After completing all the steps mentioned above know the data should be accessible it offers various ways to access and utilize your data stream.
- Kinesis Data Streams API.
- Kinesis Firehose.
- Kinesis Analytics.
What Can I Do With Kinesis Data Streams?
Amazon Kinesis will stream the data in real-time help in handling it and also tell you what to do with that data according to the organization’s goals following are the broad categories to get you started:
- Real time data ingestion and processing: Amazon kinesis will take the data from the real time it will helps in the applications like health which are used for the identifying the and regulating the health of the patient and also if any any emergency with the help of data we can predict it in before head. It can also used in the applications of OTT platforms by which you can personalize the according to the user experience.
- Streamlined data delivery and storage: The real time data can be stored in the storage and can be used for the further research and can be used for the further use and also amazon kinesis can be integrated with the other services also.
- Real-time insights and automation: The data which is collected from the real time data will be analyzed the whole data and recats to anomalies, fraud attempts or any other critical immediately. And also monitor the key metrics which can be used for the data driven decision making.
Types of Services Offered by Amazon Kinesis
There are three types of services which Amazon kinesis offers are as follows:
- Kinesis Data Firehose
- kinesis Analytics
- Kinesis Data streams
Kinesis Firehose
Firehose allows the users to load or transformed their streams of data into amazon web service latter transfer for the other functionalities like analyzing or storing. It does not require continuous management as it is fully automated and scales automatically according to the data.
Kinesis Analytics
It allows the streams of data provided by the kinesis firehose and kinesis streams to analyze and process it with the standard SQL. It analyzes the data format and automatically parses the data and by using some standard interactive schema editor to edit it in recommend schema. It also provides pre-built stream process templates that can be used to select a suitable template for their data analytics.
Kinesis streams
It provides a platform for real-time and continuous processing of data. It is also used to encrypt the sensitive data by using the KMS master keys and the server-side encryption for the security purpose.The architecture of Amazon Kinesis looks somewhat like the given below image:
Features of Amazon Kinesis
- Cost-efficient: All the services provided by the amazon are cost-efficient as it follows the pay as you go model which means you have to pay for the service according to the usage, not a flat price. So it becomes advantageous for the user s that they have to pay only what they use.
- Integrate with other AWS services: Amazon Kinesis allows users to use the other AWS services and integrate with it. Services that can be integrated are Amazon DynamoDB, Amazon Redshift, and all the other services that deal with the large amount of data.
- Availability: You can access it from anywhere and anytime. Just need a good connectivity of net.
- Real-time processing- It allows you to work upon the data which is needed to be updated every time with changes instantaneously. Most advantageous feature of Kinesis because real-time processing becomes important when you are dealing with such a huge amount of data.
Use Cases Of Amazon Kinesis
- Real-time application monitoring: Amazon kinesis will provide the real time data of the applications like if you consider the health application it will provides the live feed of the data by which you can take care of the health by which the issues that is pointed by amazon kinesis.
- Fraud detection and prevention: Amazon Kinesis will helps you to protect the data from fraudulent activity by analyzing transaction data by which you can detect the suspicious patterns and blocks fraudulent transactions before they happen.
- Personalized recommendations and marketing: Amazon kinesis will helps you in analyzing the data of the customers by which you can understand your customers very better. You can recommends the personalised products in real time to the costumers.
- IoT analytics and predictive maintenance: Your connected gadgets’ full potential is unlocked with Kinesis. Through the examination of sensor data from electronics, automobiles, or machinery.
Limits of Amazon Kinesis
- The limitation that Amazon kinesis has that it only access the stream of records log for 24 hours by default but it can extend but up to only 7 days not longer than that.
- There is no upper limit in the number of streams that can users have in their accounts.
- One shard supports up to 1000 PUT records per second.
Amazon Kinesis Video Streams
Amazon Kinesis video streams is a power tool that is provided by AWS as a service that can deliver live on-demand streams in the real-time following are some of the key features used with kinesis streams.
- Ingest live video from various sources
- Process video in real-time
- Analyze video content
- Deliver video to various destinations
- Build custom video applications
FAQs On Amazon Kinesis
1. Amazon Kinesis Data FireHose
Firehose allows the users to load or transformed their streams of data into amazon web service latter transfer for the other functionalities like analyzing or storing. It does not require continuous management as it is fully automated and scales automatically according to the data.
2. Amazon Kinesis Analytics
It allows the streams of data provided by the kinesis firehose and kinesis streams to analyze and process it with the standard SQL. It analyzes the data format and automatically parses the data and by using some standard interactive schema editor to edit it in recommend schema. It also provides pre-built stream process templates that can be used to select a suitable template for their data analytics.
3. Amazon Kinesis vs Kafka
Both Apache Kafka and Amazon Kinesis are well-known real-time data streaming systems, although they serve different purposes and have different features.