Amazon Kinesis Reviews
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6 Reviews
- Industry: Banking
- Company size: 1,001–5,000 Employees
- Used Daily for 2+ years
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Review Source
Overall rating
- Value for Money
- Ease of Use
- Customer Support
- Likelihood to recommend 10.0 /10
Message broker with amazing integration with AWS services
Reviewed on 2022/04/20
We use it as part of a streaming pipeline. It helps with back-pressure when there is a sudden burst...
We use it as part of a streaming pipeline. It helps with back-pressure when there is a sudden burst in the events and it also allows us to consume data in parallel.
Pros
easy integration with AWS lambda, kinesis firehose (s3) and third party software ( ex: splunk)
Cons
No autoscaling for now. For now we are setting alarms when there is an increase in the incoming data and then we scale it manually. We are thinking of automating this process with cloudwatch+ sns+ lambda
- Industry: Computer Software
- Company size: 51–200 Employees
- Used Daily for 1+ year
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Review Source
Overall rating
- Value for Money
- Ease of Use
- Customer Support
- Likelihood to recommend 8.0 /10
High Availability and Durability
Reviewed on 2023/03/29
Pros
When it comes to availability, durability, and scalability, it is one of the best performant products for data streaming I have already used. It can also integrate with a lot of AWS services.
Cons
Other than the expertise in streaming data it needs, it also can incur high costs depending on the data stored and processed.
- Industry: Information Technology & Services
- Company size: 201–500 Employees
- Used Weekly for 1+ year
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Review Source
Overall rating
- Value for Money
- Ease of Use
- Customer Support
- Likelihood to recommend 7.0 /10
Analytics on streaming data
Reviewed on 2023/02/18
A well built advanced analytics tool with good scalability, maintainance and integration capabilitie...
A well built advanced analytics tool with good scalability, maintainance and integration capabilities to make data more meaningful.
Pros
Used it as a basis for distributing information for IOT, multiple databases including SQL and NoSql, websites, that was used as a message queuing flow all put together. Can monitor all the IOT sensors information with its reporting and processing information. The data streaming events are fast and you can perform create, del, update and read (CRUD) operations on them, with good data retention. For the case of ML you can use it to find data anomalies.
Cons
Not much of a community base for doubt clearing, troubleshooting issues and solving problems. When went through the documentation, found it difficult to understand and confusing.
- Industry: Information Technology & Services
- Company size: 201–500 Employees
- Used Daily for 2+ years
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Review Source
Overall rating
- Value for Money
- Ease of Use
- Customer Support
- Likelihood to recommend 10.0 /10
Amazon Kinesis
Reviewed on 2023/02/25
Pros
stream the data without any error or miss any dataeasy to setup the stream from the server
Cons
there is a delay of a stream of logs when integrate with another tool it is taken at least 5 min to sync each slot.
- Industry: Retail
- Company size: 201–500 Employees
- Used Weekly for 1+ year
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Review Source
Overall rating
- Value for Money
- Ease of Use
- Likelihood to recommend 7.0 /10
Very powerful to stream data
Reviewed on 2022/11/23
Pros
Amazon Kinesis is very powerful . You can gather data quickly in a very effective way
Cons
Like lot of AWS service, it can be a bit tricky to setup and documentation can be a bit complex
- Industry: Computer Software
- Company size: 10,000+ Employees
- Used Monthly for 2+ years
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Review Source
Overall rating
- Ease of Use
- Likelihood to recommend 10.0 /10
Easy integration with other services
Reviewed on 2022/07/05
Pros
One of the best features of Amazon Kinesis is the easy integration of it with other AWS services. We often require the streaming data from Kinesis to be stored and later analyzed. This requires easy integration with services like Lambda, S3, Data lakes etc. This can be done very easily in the case of Kinesis.
Cons
There is very less visibility when the data is within AWS Kinesis. The user of the data has not idea where it resides. This is specially important in situations where there are drop in messages. Although its not an exact science Kinesis can make it better.
