Amazon Kinesis and Amazon MSK are prominent streaming data solutions in the AWS ecosystem. While Amazon Kinesis is often praised for its simplicity and quick deployment, Amazon MSK holds an advantage for users requiring extensive Kafka compatibility and operational flexibility.
Features: Amazon Kinesis offers a fully managed service for real-time data processing with features such as auto-scaling, multi-partitioning, and easy integration with AWS services like S3 and Lambda. Amazon MSK stands out for its deep integration with the Kafka ecosystem, robust support for real-time analytics, and native Kafka managed services, providing flexibility for large workloads and smooth development environments.
Room for Improvement: Amazon Kinesis could improve by simplifying data sharding, raising default throttling limits, and enhancing multi-consumer data access. Kinesis may also face challenges outside of the AWS ecosystem. Amazon MSK users express a need for smoother integrations, more configuration flexibility, and better support for external plugins.
Ease of Deployment and Customer Service: Amazon Kinesis is known for its rapid implementation within the AWS environment, offering reasonable customer support with quick response times, though sometimes lacking in depth. Amazon MSK also offers flexible deployment but may require more initial configuration due to its Kafka base. Its technical support receives good feedback, but there is room for increased efficiency and responsiveness.
Pricing and ROI: Amazon Kinesis is seen as cost-effective with a clear pricing structure, though costs can increase with heavy usage. Users highlight significant ROI from reduced infrastructure overhead. Amazon MSK may have higher initial costs for small-scale deployments but offers competitive pricing for larger workloads, providing substantial savings compared to self-managed Kafka clusters.
With Lambda, there is no need for data transfer charges, which is beneficial for less frequent workloads.
We receive prompt support from AWS solution architects or TAMs.
They can manage most of our queries, and for what they cannot manage, they guide us through the process of finding out.
Amazon's support is excellent.
Amazon Kinesis provides auto-scaling with streams that handle large volumes well.
I would rate the scalability of Amazon Kinesis as a nine.
The functionality for scaling comes out of the box and is very effective.
As a B2B enterprise client, our clientele consists of large ticket clients but low amounts of users.
I would rate the stability of Amazon Kinesis as high, giving it a 10.
It doesn't require any maintenance on my end yet, as I haven't had any issues.
There is no lack of functions in Amazon Kinesis. Functionality-wise, we feel it's complete.
Amazon Kinesis could improve its pricing to be more competitive, especially for large volumes.
There are preset configurations and limited configurations that we can set for our unique use case.
I had to remove and drop all the clusters and recreate them again, which is complicated in a production environment.
The increase in cloud costs by 50% to 60% does not justify the savings.
Amazon Kinesis and Lambda pricing is competitive, but we noticed that scaling and large volumes could potentially increase costs significantly.
We use Kafka M5 Large instance, and depending on the instances, that is the cost we have, along with storage cost and data transfer costs.
Once we started using Kafka, our cloud costs rose by 50% to 60%.
Lambda's scalability, seamless integration with other AWS services, and support for multiple programming languages are very beneficial.
Amazon Kinesis integrates easily with the AWS environment.
The scalability and usability are quite remarkable.
The best features of Amazon MSK are the real-time analytics that are excellent.
It starts checking how the brokers are functioning, and automatically, Amazon MSK tries to resolve all the problems.
| Product | Market Share (%) |
|---|---|
| Amazon Kinesis | 5.4% |
| Amazon MSK | 5.1% |
| Other | 89.5% |
| Company Size | Count |
|---|---|
| Small Business | 8 |
| Midsize Enterprise | 10 |
| Large Enterprise | 9 |
| Company Size | Count |
|---|---|
| Small Business | 4 |
| Midsize Enterprise | 7 |
| Large Enterprise | 4 |
Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. Amazon Kinesis offers key capabilities to cost-effectively process streaming data at any scale, along with the flexibility to choose the tools that best suit the requirements of your application. With Amazon Kinesis, you can ingest real-time data such as video, audio, application logs, website clickstreams, and IoT telemetry data for machine learning, analytics, and other applications. Amazon Kinesis enables you to process and analyze data as it arrives and respond instantly instead of having to wait until all your data is collected before the processing can begin.
Amazon Managed Streaming for Apache Kafka (Amazon MSK) is a fully managed service that enables you to build and run applications that use Apache Kafka to process streaming data. Amazon MSK provides the control-plane operations, such as those for creating, updating, and deleting clusters.
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