Kafka vs Kinesis – What’s the Difference? (Pros and Cons)
Kafka vs Kinesis – What’s the Difference? (Pros and Cons). So Kafka and Kinesis are event streaming software tools which collect tons of data and logs for real time streaming. Both tools can help you view changes made on data, integrate with open source apps and can analyse data in real time. These tools enable users to collect and process large streams of data.
This article compares Apache Kafka and Amazon Kinesis based on a range of features.
So shall we proceed with Kafka vs Kinesis – What’s the Difference? (Pros and Cons)
What is Kafka?
Firstly Kafka is an open source event streaming software that can help process terabytes of data pipelines in real time. Also with Kafka it has batch processing capabilities and various use cases for manufacturers, banks and insurance. Secondly Kafka is powered by the community and configured on Apache. In addition Kafka is written in Scala and Java programming languages.
How Kafka Works
Here with Kafka’s architecture it relies on the consumer library and producer library. An input of data streams into Kafka goes through record buffers and state stores. This data goes through a producer library to produce an output Kafka stream.
The tool has a messaging layer to partition streams and tasks. In addition, users can configure parallel threads for instance processing. The state store keeps data from stateful workloads. Native capabilities of Kafka include the consumer client, which remediates failures. Moreover Kafka has data record keys to define data routing to topic partitions.
Features of Kafka
Evidently Kafka is one of the best stream analytics software in the event streaming category. The most distinctive features on Kafka include:
- Open source has higher throughput metrics at low latencies of 2ms. In essence, this leads to faster real time batch processing jobs.
- Architecture of Kafka allows for scaling. You can process trillions of requests and bytes daily without overloading the system.
- Fault tolerant consumer client to maximize availability and safely back up workloads.
- Distributes your data across servers in various availability regions. This improves availability in several geographical locations.
- Uses built in event processing and streaming features. Ideally, these do not require added APIs, integrations and microservices.
Pros of Kafka
Worth adding that Kafka has good DevOps management capabilities. These include backup, disaster recovery and clustering capabilities. Other advantages of Kafka include:
- This tool has a higher throughput metric compared to the competition.
- Both consumer and producer libraries allow Kafka to offer features beyond a messaging platform, for example, KSQL processing.
- You can run multiple workloads and stream events in real time.
- All Kafka products come in an easy to use fashion. In essence, it supports multiple frameworks and programming languages like Python, Java, and Scala.
Cons
- The tool lacks a GUI to help debug problems within topics
- Has steeper learning curve for new beginners.
Now with this article Kafka vs Kinesis – What’s the Difference? it is time to get to know Kinesis.
What is Kinesis?
Amazon Kinesis is an AWS event streaming package offering real time data and video analysis streams. With Amazon Kinesis it streams various forms of data, including videos, logs, audios, and many more. Also the Equally important to add that Kinesis uses Machine learning and telemetry technology for accurate analysis. Kinesis has several product offerings:
- Data Streams for collecting, storing, and storing big data jobs.
- Data Firehose uses BI tools for real time analysis of AWS data stores.
- Video Streams for video stream analytics.
- Data Analytics analyses data using no code SQL and Apache Flink services.
How Kinesis Works
Each Kinesis tool has a different architecture. The main difference is on the destination of the data stream. More to add with AWS Kinesis is that it uses an input processing output model. The nature of input depends on the type of data, for example, video data goes to Kinesis Video streams.
Here is a summary of how Kinesis works:
- Kinesis Video streams gives an output in real-time.
- Kinesis data streams let you make apps with Kinesis Data Analytics, Spark EMR, EC2 and AWS Lambda.
- The Data Firehose stores data on AWS S3, Redshift and Splunkon before output.
- Data Analytics integrates with your favorite output tools.
Features of Kinesis
Here are some features that make Kinesis a top streaming platform:
- Video streams of Kinesis let users stream video from security cameras and IoT devices to AWS platforms. Additionally Kinesis has added facial recognition features to improve home security.
- Has real time data processing capabilities. There’s no need to store data before analysing.
- Clickstream analytics features can stream website clicks in real time to help enhance eCommerce sales.
- It lets users build real time applications with other AWS services like EC2, AWS Lambda, and EMR.
Pros of Kinesis
Some of the benefits of using Amazon Kinesis include:
- Quick data processing jobs with the ability to share streams with other applications.
- Easy to use GUI and added tutorials to solve problems without coding.
- High scalability .
- You can run multiple workloads while minimizing costs.
- Stores data for up to 24 hours, and users can easily change configurations from the EC2 portal.800
Cons
Whilst Kinesis has numerous advantages, it also has some downsides. These include:
What are The Differences Between Kafka and Kinesis?
Here are some key differences between Apache Kafka and Amazon Kinesis:
Pricing
Being an open source tool, Apache Kafka is free. However, there are added costs of resource provisioning, cluster management and configurations.
On the other hand Amazon Kinesis is a paid service unless you’re on the AWS free tier. However, AWS costs decrease over time when you choose a reservation pricing model. Amazon, being a public cloud offering, is more expensive to set up, run and maintain compared to Kafka.
Management
Here the Kafka’s installation needs on premise facilities. Users have to manage data clusters and hardware. Oppositely , Kinesis is easy to use. AWS users can easily customize Kinesis even with basic skill set.
Use Cases
Use cases of Kafka make it ideal for distributed system engineers. You can perform several workloads like clustering, auto scaling and event streaming using Kafka’s native abilities. But Amazon kinesis works well for app development, web development, and IoT use cases. You can easily integrate with AWS EC2, RDS, and other third party tools.
Security
Security in Kafka authenticates broker connections via secure links. However, Kafka’s security requires advanced understanding of the command line language. Interestingly AWS has enterprise grade security for Kinesis users. Users can easily secure workloads using encryption, master keys and VPC.
Products
Products with Apache Kafka, there are 2 main products: Kafka Connect and Kafka Streams. For example Kinesis has 4 product offerings including Video streams, Data streams, Data analytics and data firehose.
Performance
How about performance of both? With Apache Kafka the users have more data writing options. This is because it handles huge volumes of real-time data streams and high throughput. On the other hand, Kinesis users can synchronize data to three data centers at a time.
Scalability
There is no downtime on all its dimensions with Apache Kafka: scales distributed systems efficiently without ; connectors, processors, producers and consumers. Besides Apache Kafka handles any amount of streaming data from numerous sources with low latency. Comparatively, with Kinesis Data Streams, you can’t scale more than ten times per rolling 24-hour period per stream.
You have reached the end of an article blog Kafka vs Kinesis – What’s the Difference? (Pros and Cons).
Kafka vs Kinesis - What's the Difference ? (Pros and Cons)- Conclusion
You can rely on either tool for real time streaming. Each tool has unique features, advantages and downsides. Evidently Amazon Kinesis supports various programming languages compared to Apache Kafka. On the other hand, Kafka is an ideal option for advanced streaming and data analytics. Finally Amazon Kinesis has easy to understand tutorials and support for beginners.
While Kafka is a cheaper alternative and stores data for longer periods, it requires complex initial configurations. If you just want a robust solution, choose Kafka. However, if you’re a beginner in event streaming choose Amazon Kinesis. Nonetheless Kinesis can also handle advanced workloads. Overall AWS takes care of security and maintenance while you focus on productivity.
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