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
Heap
Score 8.2 out of 10
Mid-Size Companies (51-1,000 employees)
Heap is a web analytics platform captures every user interaction on web iOS with no extra code. The tool allows you to track events and set up funnels to understand user flow and dropoff. It also provides visualization tools to track trends over time.
$0
per month
Pricing
Amazon Kinesis
Heap
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
Free
$0
Up to 10k sessions/month
Growth
Starting at $3,600 annually
Up to 300k sessions/year
Pro
Contact Heap Sales
Custom sessions per month and unlimited projects
Premier
Contact Heap Sales
Custom sessions per month
Offerings
Pricing Offerings
Amazon Kinesis
Heap
Free Trial
No
Yes
Free/Freemium Version
No
Yes
Premium Consulting/Integration Services
No
Yes
Entry-level Setup Fee
No setup fee
Optional
Additional Details
—
Heap pricing is based on session volume. A session is a period of activity from a single user on your app or website. It can include many pageviews or events.
More Pricing Information
Community Pulse
Amazon Kinesis
Heap
Features
Amazon Kinesis
Heap
Streaming Analytics
Comparison of Streaming Analytics features of Product A and Product B
Amazon Kinesis is a great replacement for Kafka and it works better whenever the components of the solution are AWS based. Best if extended fan-out is not required, but still price-performance ratio is very good for simplifying maintenance.
I would go with a different option if the systems to be connected are legacy, for instance in the case of traditional messaging clients.
Scenarios when Heap was well suited: It is when a user claims that he encountered a bug without giving us the details of the error message. Scenarios where it is less appropriate: Its when we try to capture user interaction in our mobile app
It's a great platform. I'm glad that one of our product managers introduced it because it has allowed us to create all kinds of new functionality. We're not only able to create a better product experience from our communications because of Heap, but we're also able to generate all kinds of helpful analysis.
On a scale from 1-10, I find Heap to be incredibly user-friendly and easy to use. I enjoyed the training videos available and was quickly able to pick up how to create events and reports to track user interactions on our product. I would recommend Heap for its usability first and foremost.
I've never run into any issues with Heap's availability, Heap is always there when I need it. I haven't run into any issues like application errors or unplanned outages during my 2+ years of using Heap. Each and every time I log in to Heap I have a completely functional experience
Heap doesn't affect page load times considerably nor has a large impact [on] our overall score, as far as page loading times inside of the tool its pretty reliable to retrieve data as much as "instant" that it can be the delay seems to be on data getting tracked into the servers to be read but it's not significant.
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.
Heap support has allowed us to troubleshoot and test a lot of different items. Their support team is always helpful and friendly, even when we come to them with the most complicated questions. I think this greatly improves the value proposition of the product because their support team is knowledgable and friendly.
The implementation was smooth and easy. The Heap team helped us with implementation and it went great! Within a few weeks, we were fully up and running and utilizing the platform to its full capability. This is an additional thing that has made this platform so great and we couldn't recommend it enough.
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 cases, with low latency, higher volume of data, real time decisions and integration with multiple sources and destination at a decent price, Kinesis is better.
Heap offers a ton of functionality on a single platform.It also has an smart data science layer to offers suggestions for next steps in the analysis, allowing us to explore alternative paths we may not think to take. The low-code option for updating data is appealing, and there is a lot of automation with minimal engineering effort.
The most challenging part of using Heap in a growing organization is the naming and structure in which reports and dashboards are organized. I work within the marketing department and our Heap leader internally works within the IT/Product department, which makes it challenging because we often don't speak the same language, so the learning curve has been steep without any specific use-case examples to leverage online.
