Amazon Kinesis vs. jKool

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Amazon Kinesis
Score 9.9 out of 10
N/A
Amazon Kinesis is a streaming analytics suite for data intake from video or other disparate sources and applying analytics for machine learning (ML) and business intelligence.
$0.01
per GB data ingested / consumed
jKool
Score 7.0 out of 10
N/A
jKool is a streaming analytics platform from the company of the same name in Melville, that analyzes fast data such as logs, metrics, transactions in real-time so users can focus on finding insight and opportunities in their data.N/A
Pricing
Amazon KinesisjKool
Editions & Modules
Amazon Kinesis Video Streams
$0.00850
per GB data ingested / consumed
Amazon Kinesis Data Streams
$0.04
per hour per stream
Amazon Kinesis Data Analytics
$0.11
per hour
Amazon Kinesis Data Firehose
tiered pricing starting at $0.029
per month first 500 TB ingested
No answers on this topic
Offerings
Pricing Offerings
Amazon KinesisjKool
Free Trial
NoNo
Free/Freemium Version
NoNo
Premium Consulting/Integration Services
NoNo
Entry-level Setup FeeNo setup feeNo setup fee
Additional Details
More Pricing Information
Community Pulse
Amazon KinesisjKool
Considered Both Products
Amazon Kinesis
Chose Amazon Kinesis
Kinesis is oriented to streaming in a scalable way large volumes of information in real-time. Glue is more an ETL so it is not well suited for real-time applications while Beanstalk is more a simple container platform. Lambda could do the job but it would require a lot of …
Chose Amazon Kinesis
The main benefit was around set up - incredibly easy to just start using Kinesis. Kinesis is a real-time data processing platform, while Kafka is more of a message queue system. If you only need a message queue from a limited source, Kafka may do the job. More complex use …
Chose Amazon Kinesis
Actually we didn't select Kinesis, we were forced into using it because SQS wasn't yet supported by Lambda. Unlike Kinesis, SQS supports both FIFO and standard queues which let us control order of events processed, as well as handle retry logic, failover logic, and set up …
jKool
Chose jKool
No other product that I used is similar to jKool, it's unique product that have good amount of features that I would be opened to invest more in the future if time permit. It still has a long way to go and the first thing it can do is clean up it user interface to make it better.
Features
Amazon KinesisjKool
Streaming Analytics
Comparison of Streaming Analytics features of Product A and Product B
Amazon Kinesis
8.3
Ratings
6% above category average
jKool
7.0
Ratings
11% below category average
Real-Time Data Analysis10.00 Ratings7.00 Ratings
Data Ingestion from Multiple Data Sources9.00 Ratings7.00 Ratings
Low Latency9.00 Ratings6.00 Ratings
Integrated Development Tools9.00 Ratings7.00 Ratings
Data wrangling and preparation10.00 Ratings6.00 Ratings
Linear Scale-Out6.10 Ratings8.00 Ratings
Data Enrichment5.00 Ratings9.00 Ratings
Visualization Dashboards00 Ratings5.00 Ratings
Machine Learning Automation00 Ratings8.00 Ratings
Best Alternatives
Amazon KinesisjKool
Small Businesses
IBM Streams (discontinued)
IBM Streams (discontinued)
Score 9.0 out of 10
IBM Streams (discontinued)
IBM Streams (discontinued)
Score 9.0 out of 10
Medium-sized Companies
Tealium Customer Data Hub
Tealium Customer Data Hub
Score 8.5 out of 10
Tealium Customer Data Hub
Tealium Customer Data Hub
Score 8.5 out of 10
Enterprises
Spotfire Streaming
Spotfire Streaming
Score 5.1 out of 10
Spotfire Streaming
Spotfire Streaming
Score 5.1 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Amazon KinesisjKool
Likelihood to Recommend
9.0
(0 ratings)
7.0
(0 ratings)
Support Rating
7.1
(0 ratings)
-
(0 ratings)
User Testimonials
Amazon KinesisjKool
Likelihood to Recommend
Perfect for real-time data processing and streaming. Also, there's no need for any specific setup - you just start using it immediately and it easily integrates with the rest of AWS capabilities (like Redshift), although integration with Lambda could be better. You can make your overall analytics landscape way simpler with Kineses even if you have non-Amazon solutions like Tableau. It all integrates really well!
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JKool is a decent tool for retrieving information regarding user engagement and customer feedback for your software products. With these information it's very valuable stepping stone for us to make future updates or produce new products. However, there are some downsides with jKool, two of which are there are too much clutter in the GUI and it takes sometimes to turn how things work.
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Pros
  • Integrating with other Amazon services
  • Scaling requests
  • Totally serverless platform
  • Simple management
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No answers on this topic
Cons
  • Improve integration with AWS Lambda
  • Some duplicate records coming from the stream
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No answers on this topic
Support Rating
The documentation was confusing and lacked examples. The streams suddenly stopped working with no explanation and there was no information in the logs. All these were more difficult when dealing with enhanced fan-out. In fact, we were about to abort the usage of Kinesis due to a misunderstanding with enhanced fan-out.
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Alternatives Considered
Kinesis is oriented to streaming in a scalable way large volumes of information in real-time. Glue is more an ETL so it is not well suited for real-time applications while Beanstalk is more a simple container platform. Lambda could do the job but it would require a lot of programming to accomplish the same as Kinesis. In fact, our solution employed the four elements for different tasks but using Kinesis as the message bus.
Read full review
No other product that I used is similar to jKool, it's unique product that have good amount of features that I would be opened to invest more in the future if time permit. It still has a long way to go and the first thing it can do is clean up it user interface to make it better.
Read full review
Return on Investment
  • Caused us to need to re-engineer some basic re-try logic
  • Caused us to drop some content without knowing it
  • Made monitoring much more difficult
  • We eventually switched back to SQS because Kinesis is not the same as a Queue system
Read full review
No answers on this topic
ScreenShots