Find out in this report how the two Streaming Analytics solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.
With Lambda, there is no need for data transfer charges, which is beneficial for less frequent workloads.
The incidents have disappeared completely since I have been using Striim.
Since it is now one to two hours, I would say it has saved employee hours and time.
Time savings are crucial since it saves considerable time, which positively impacts the return on investment.
We receive prompt support from AWS solution architects or TAMs.
Since it originated from Oracle GoldenGate, the customer service, support, or whatever help is required is the best.
They are all knowledgeable about what they do.
When you contact them, they give you a response straight away and help you identify the issue and fix it.
Amazon Kinesis provides auto-scaling with streams that handle large volumes well.
I would rate the scalability of Amazon Kinesis as a nine.
Our licensing was based on the number of cores, so even if we have a high number of events on any given day, our license cost would not go high.
When it comes to scaling with Striim as workloads increase, it has been quite helpful and could adapt easily, saving considerable time in delegation and follow-up because I only need to roll back scripts to ensure that nothing goes wrong.
I would describe the scalability of Striim as very good, as it adapts well.
I would rate the stability of Amazon Kinesis as high, giving it a 10.
That problem has been completely resolved with Striim.
Striim was very stable.
Striim has proven stable in my experience, as I have not encountered any downtime or disruptions.
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.
I believe if Striim could use some part of AWS secrets or its own secret mechanism to store the password, that would really save a lot of time so that I don't have to keep updating the password whenever there is any change.
They could improve the documentation by showing how to configure with different platforms.
Striim can be improved by providing tools such as short videos or step-by-step manuals to clearly demonstrate its capabilities and help users learn quickly.
Amazon Kinesis and Lambda pricing is competitive, but we noticed that scaling and large volumes could potentially increase costs significantly.
Licensing was a bit more expensive because Striim has to read from Oracle GoldenGate trail files and also integrate them.
My experience with pricing, setup cost, and licensing is that it is costly.
My experience with the pricing, implementation cost, and licensing of Striim is that it is somewhat expensive.
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.
Striim is capable of absorbing a large number of transactions, and the difference between the two databases is always less than a second, which demonstrates efficiency.
There were significant improvements because once we enabled change data capture, the database was not going down at all.
It reduces manual intervention because it automatically syncs the data from the warehouse.
| Product | Mindshare (%) |
|---|---|
| Amazon Kinesis | 3.9% |
| Striim | 1.9% |
| Other | 94.2% |
| Company Size | Count |
|---|---|
| Small Business | 8 |
| Midsize Enterprise | 10 |
| Large Enterprise | 10 |
| Company Size | Count |
|---|---|
| Small Business | 2 |
| Large Enterprise | 5 |
Amazon Kinesis provides real-time data streaming with seamless AWS integration, ideal for analytics, data transformation, and external customer feeds. It offers cost-effective data management with high throughput and low latency, supporting multiple programming languages.
Amazon Kinesis enables organizations to manage real-time data streams efficiently. Its integration with AWS ensures seamless setup and operation, while features like auto-scaling and fault tolerance make it reliable for diverse data sources such as IoT devices and server logs. The platform's ability to handle large-scale event-driven systems and dynamic workloads makes it suitable for complex streaming architectures. Despite some challenges with costs and setup complexity, Kinesis remains a popular choice for its efficient data management and processing capabilities.
What are the key features of Amazon Kinesis?In industries such as IoT, finance, and entertainment, Amazon Kinesis facilitates the real-time ingestion and processing of data streams. It connects seamlessly to data lakes and warehouses, enabling businesses to harness data-driven insights without performance loss. This capability is essential for managing dynamic workloads and large-scale event systems. By supporting tools like KDS, Firehose, and Video Streams, Kinesis empowers organizations to respond quickly to changing data environments, enhancing operational effectiveness across different sectors.
Striim offers a comprehensive platform for real-time data integration and streaming analytics, designed to streamline data processes for enterprise-level solutions.
Striim enables seamless migration and integration of data across cloud and on-premises environments, making it ideal for businesses looking to leverage real-time analytics. Its capabilities support continuous data flow, reducing latency and enhancing decision-making. Designed for scalable and secure data management, Striim facilitates effective data-driven strategies.
What are some key features of Striim?In industries like finance, Striim supports real-time fraud detection by providing uninterrupted data streaming between transaction systems. In healthcare, it enables rapid data processing for patient monitoring, improving service delivery. Manufacturing uses Striim to enhance supply chain visibility through real-time data analytics.
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