Amazon Kinesis Reviews

We do data acquisition based on what is pumped from the remote data and process it centrally so that we may present to our customers meaningful reports, charts, additional layers of support, or alerts. 

At the moment, I am not using Amazon Kinesis, but Azure Event Hub, which I have found to be more meaningful and easier to use. 

I like the event bubbling feature of Amazon Kinesis, although I ultimately switched to Azure Event Hub. Both solutions have similar features, but the latter offers us certain operational advantages. 

Amazon Kinesis is not a bad product, but Azure Event Hub provides us with certain operational advantages, as our focus is on Microsoft related coding. This is why .NET is what we use at the backend. While we can use both Azure Event Hub and Amazon Kinesis towards this end, I feel the latter to be less customized or developed for use in connection with the server-less programming.

Amazon Kinesis has a less meaningful and easy use than Azure Event Hub. 

Amazon Kinesis involved a more complex setup and configuration than Azure Event Hub. 

I have been using Amazon Kinesis for the past year, although I have since switched to Azure Event Hub. 

The scalability is pretty good. One can have any number of nodes spawned or replicated on the primary. Any load can be handled, perhaps a few terabytes with ease in around 15 seconds. One can scale up to this. 

While we have not had occasion to contact Amazon tech support concerning the solution, we have in relation to other matters. We felt it to be good. 

The initial setup and configuration of Amazon Kinesis was more involved than that of Azure Event Hub. 

The solution's pricing is fair. The trick lies in Amazon's pricing. They charge according to the different layers of or types of data that is transfered.

In addition to Azure Event Hub, we also have experience with Apache Kafka, which I feel to offer greater power but more complex configuration. This solution has more features for a variety of purposes. 

The question of whether I would recommend Amazon Kinesis over Azure Event Hub is tricky. While both have their advantages and I consider them to be almost equal, we feel the latter to be better suited to our environment, which is why we went with it. The data transferring policies and associated costs of Amazon were the deciding factors for me.

I rate Amazon Kinesis as an eight or nine out of ten. 

We use this solution for quite large environments.

We use it to capture and process a lot of data. We use it, for example for data analytics and query and analyze a stream's data.

We are a sizable organization and as such, have a lot of data. The solution allows for real-time analysis and you can use a scaler to handle data flows. 

The solution is very flexible and allows for a lot of configuration. It just offers up a lot of possibilities.

I'm using Amazon S3 and Redshift using Amazon server. I can make large configurations and update in near real-time, so that we have real-time use for batch intervals. 

The solution is great for scanning in order to handle environmental data.

The data stream feature on offer is excellent. We use it quite extensively.

The solution works well in rather sizable environments. We deal with a lot of data and it handles it very well.

The solution has a very good alerts system to allow us to respond in real-time.

The dashboards are excellent.

The solution offers very good data capture and integrates well with Power BI and Tableau, for example.

The product makes it very easy to create jobs.

The automation could be better. The solution needs to be better at information capture.

Some jobs have limitations which can make the process a bit challenging.

In order to do a successful setup, the person handling the implementation needs to know the solution very well. You can't just come into it blind and with little to no experience.

I've used the solution for six or seven years or so.

We work with very large environments and haven't had any issues with feeling constricted by the solution.

Personally, based on my past experience and my long history with the solution, the initial setup was not complex. It was pretty straightforward. I find it very easy to use these tools.

A user will need to understand how to create analytics using processing a large amount of information. There may be legacy solutions in the mix as well. A new user will need to understand the environment and all of the requirements before really digging in.

What I will need, basically, is a data map, where I can find any legacy data. From there I can do the setup and it goes pretty smoothly.

I handle the implementation myself.

You can compare this solution to Data Factory and Hadoop. They have a few overlapping characteristics. However, for my industry, Hadoop, for example, wouldn't work as it was lacking some characteristics and parameters and some understanding of the industry itself.

I have a lot of experience in Kinesis and data analytics including in networking in the Amazon AWS environment. My experience is as a big data architect. I draw all environments in AWS. 

On a scale from one to ten, I would rate the solution at a six. It's pretty good, and great for big environments, however, you do need to be well versed in the product to set it up.