Amazon Kinesis vs. Apama Community Edition

Overview
ProductRatingMost Used ByProduct SummaryStarting Price
Amazon Kinesis
Score 9.6 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
Apama Community Edition
Score 7.0 out of 10
N/A
Apama Streaming Analytics is a platform for streaming analytics and intelligent automated action on fast-moving big data. Combining event processing, messaging, in-memory data management and visualization, this platform is presented as a complete solution to turn relentless data streams—like those produced by the Internet of Things (IoT)—into meaningful real-time metrics. It's community edition is still available, the commercial edition is not.N/A
Pricing
Amazon KinesisApama Community Edition
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
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Offerings
Pricing Offerings
Amazon KinesisApama Community Edition
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 KinesisApama Community Edition
Features
Amazon KinesisApama Community Edition
Streaming Analytics
Comparison of Streaming Analytics features of Product A and Product B
Amazon Kinesis
8.3
Ratings
3% above category average
Apama Community Edition
-
Ratings
Real-Time Data Analysis10.00 Ratings00 Ratings
Data Ingestion from Multiple Data Sources9.00 Ratings00 Ratings
Low Latency9.00 Ratings00 Ratings
Integrated Development Tools9.00 Ratings00 Ratings
Data wrangling and preparation10.00 Ratings00 Ratings
Linear Scale-Out6.10 Ratings00 Ratings
Data Enrichment5.00 Ratings00 Ratings
Best Alternatives
Amazon KinesisApama Community Edition
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
Confluent
Confluent
Score 9.9 out of 10
Confluent
Confluent
Score 9.9 out of 10
Enterprises
Spotfire Streaming
Spotfire Streaming
Score 6.6 out of 10
Spotfire Streaming
Spotfire Streaming
Score 6.6 out of 10
All AlternativesView all alternativesView all alternatives
User Ratings
Amazon KinesisApama Community Edition
Likelihood to Recommend
9.0
(0 ratings)
-
(0 ratings)
Support Rating
7.1
(0 ratings)
-
(0 ratings)
User Testimonials
Amazon KinesisApama Community Edition
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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Pros
  • Integrating with other Amazon services
  • Scaling requests
  • Totally serverless platform
  • Simple management
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Cons
  • Improve integration with AWS Lambda
  • Some duplicate records coming from the stream
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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.
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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
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ScreenShots