Amazon Kinesis Overview

Amazon Kinesis is the #3 ranked solution in our list of Streaming Analytics tools. It is most often compared to Apache Flink: Amazon Kinesis vs Apache Flink

What is Amazon Kinesis?

Amazon Kinesis makes it easy to collect, process, and analyze real-time, streaming data so you can get timely insights and react quickly to new information. Amazon Kinesis offers key capabilities to cost-effectively process streaming data at any scale, along with the flexibility to choose the tools that best suit the requirements of your application. With Amazon Kinesis, you can ingest real-time data such as video, audio, application logs, website clickstreams, and IoT telemetry data for machine learning, analytics, and other applications. Amazon Kinesis enables you to process and analyze data as it arrives and respond instantly instead of having to wait until all your data is collected before the processing can begin.

Amazon Kinesis is also known as Amazon AWS Kinesis, AWS Kinesis, Kinesis.

Amazon Kinesis Buyer's Guide

Download the Amazon Kinesis Buyer's Guide including reviews and more. Updated: July 2021

Amazon Kinesis Customers

Zillow, Netflix, Sonos

Amazon Kinesis Video

Pricing Advice

What users are saying about Amazon Kinesis pricing:
  • "Under $1,000 per month."

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MR
Senior Software Engineer at a tech services company with 501-1,000 employees
Real User
Top 5
Easily replay your streaming data with this reliable solution

What is our primary use case?

In the simpler use case, we were just pumping in some data. We wanted a product, an AWS service, that would accept data in bursts. We were pushing in, for example, 500 records every 300 milliseconds. What I'm trying to say is per second we were trying to pump in around 1,500 records into some streaming services what we were looking at. That type of streaming information would then go into another source, for example Lambda. Then Lambda would consume the data and ultimately we would process and store it in DynamoDB. This was the basic flow that we had. We were looking for a service. And at that… more »

Pros and Cons

  • "The feature that I've found most valuable is the replay. That is one of the most valuable in our business. We are business-to-business so replay was an important feature - being able to replay for 24 hours. That's an important feature."
  • "In general, the pain point for us was that once the data gets into Kinesis there is no way for us to understand what's happening because Kinesis divides everything into shards. So if we wanted to understand what's happening with a particular shard, whether it is published or not, we could not. Even with the logs, if we want to have some kind of logging it is in the shard."

What other advice do I have?

With my limited exposure to Kinesis, and with the pain points and probably not using it properly, we did see that it was successful. Having said all that, and the pain points that we went through, on a scale of one to ten I would give Kinesis an eight out of 10.
Pablo Giner
Head of BI at Wind Mobility
Real User
Top 5
The ability to have one single flow of inputting data from multiple consumers simplified our architecture

What is our primary use case?

In terms of use cases, it depends of which component we're talking about, as we use three of the 4 components. The only one we don't use is the Video Streams. Kinesis Data Stream is the module that we have been using the longest, essentially we use it to hold data which will be processed by multiple consumers. We have multiple data sources and we use Kinesis to funnel that data which is then consumed by multiple other consumers. We gather data coming from IoT devices, user phones, databases and a variety of other sources and then, as we have multiple consumers, we use Kinesis to actually… more »

Pros and Cons

  • "Amazon Kinesis has improved our ROI."
  • "Something else to mention is that we use Kinesis with Lambda a lot and the fact that you can only connect one Stream to one Lambda, I find is a limiting factor. I would definitely recommend to remove that constraint."

What other advice do I have?

My recommendation for Data Streams is to do a deep dive into the documentation before implementing to avoid what we did at the beginning. You try to process record by record or push record by record into Kinesis and then realize that it is not cost effective or even efficient. So you need to know that you need to aggregate your data before you push it into Kinesis. So documenting yourself about the best practices in using Kinesis is definitely something I would recommend to anyone. For Kinesis Analytics, I was actually surprised at how easy it is to use an application with such power. I would…
Learn what your peers think about Amazon Kinesis. Get advice and tips from experienced pros sharing their opinions. Updated: July 2021.
523,535 professionals have used our research since 2012.
ITCS user
Senior Software Engineer at a computer software company with 201-500 employees
Real User
Top 5
Fast solution that saves us a lot of time

What is our primary use case?

I work as a senior software engineer in eCommerce analytics company, we have to process a huge amount of data. Only a few people within our organization use Kinesis. My team, which includes three backend developers, simply wanted to test out different approaches. We are now in the middle of migrating our existing databases in MySQL and Postgres, to Snowflake. We use Kinesis Firehose to ingest data in Snowflake at the same time that we ingest data in MySQL, without it impacting any performance. If you ingest two databases in a synchronous way, then the performance is very slow. We wanted to… more »

Pros and Cons

  • "Amazon Kinesis also provides us with plenty of flexibility."
  • "I think the default settings are far too low."

What other advice do I have?

If you want to use a stream solution you need to evaluate your needs. If your needs are really performance-based, maybe you should go with Kafka, but for near, real-time performance, I would recommend Amazon Kinesis. If you need more than one destination for the data that you are ingesting in the stream, you will need to use Amazon Kinesis Data Streams rather than Firehose. If you only want to integrate from one point to another, then Kinesis Firehose is a considerably cheaper option and is much easier to configure. From using Kinesis, I have learned a lot about the synchronous way of…
Jeff Levy
Senior Engineering Consultant at a tech services company with 201-500 employees
Real User
Top 10
Easy to implement and use, with a robust and fault-tolerant data capturing facility

What is our primary use case?

As part of my interest in obtaining Amazon certification and learning more about Kinesis, I am currently using it to capture streaming Twitter data. I get an avalanche of tweets and I need some technology to harness and capture them. I have used the streaming Twitter API to deal with it. Twitter is updated every half a second, so I'm tapping into the streaming API and capturing a lot of stuff. It has also been used for the Internet of Things (IoT), where there is a lot of streaming stuff that comes out and you need a mechanism to capture all of it from your devices. This includes things such… more »

Pros and Cons

  • "The most valuable feature is that it has a pretty robust way of capturing things."
  • "If there were better documentation on optimal sharding strategies then it would be helpful."

What other advice do I have?

My advice for anybody who is implementing this product is to start by reading through the Amazon documentation, as well as go through some videos on YouTube or Pluralsight just to get a high-level idea of what's going on. Then, start experimenting and trying to figure out how it works. From there, try to figure out how to choose your optimal sharding strategy, like how many shards do you need within the stream and how you want to partition the data within it. I think from there, you need to look at your production and consumption rates on the stream. This is how much data you are putting onto…
Matt Newman
Principal Data Engineer at a transportation company with 1,001-5,000 employees
Real User
Top 5
A great managed service that's simple and easy to maintain

What is our primary use case?

Our primary use case of this solution is for a streaming bus architecture, we get events and they come in through Kinesis like a Jason event. It's usually a change to a database, but it can be any event such as in our application, which feeds into the Kinesis and then we have a Lambda that consumes them and then finally it puts those into a data warehouse which is the ultimate goal. So it's a near real-time data warehouse.

Pros and Cons

  • "Everything is hosted and simple."
  • "Could include features that make it easier to scale."

What other advice do I have?

It's nice to deploy this with the Amazon goodness of Cloud Formation and Terraform, to have it all deployed in a repeatable way. I know that it's easy to go into the console and do it manually, but it's best to do infrastructure as code, in particular with Kinesis. I would rate this solution a nine out of 10.
Pagidal Venkata Subba Reddy
Data Engineer
Real User
Top 5
User friendly and feature rich solution

What is our primary use case?

One use case is consuming sales data and then writing it back into the S3. That's one small use case that we have; from data Shields to data Firehose, from data Firehose to Amazon S3. There are OneClick data streams that are coming in. For click streams data we established Kinesis data streams and then from Kinesis data streams, we dump data into the S3 using Kinesis Data Firehose. This is the main use case that we have. We did many POC's on Kinesis, as well. Also, one more live project using the DynamoDB database is running in Amazon. From DynamoDB we have triggers that automatically trigger… more »

Pros and Cons

  • "Its scalability is very high. There is no maintenance and there is no throughput latency. I think data scalability is high, too. You can ingest gigabytes of data within seconds or milliseconds."
  • "Kinesis Data Analytics needs to be improved somewhat. It's SQL based data but it is not as user friendly as MySQL or Athena tools."

What other advice do I have?

My advice to anyone thinking about Amazon Kinesis, is that if they have ClickStream or any streaming data which varies from megabytes to gigabytes, they can definitely go for Amazon Kinesis. If they want to do data processing, or batch or streaming analytics, they can choose Amazon Kinesis. And if you want to enable database stream events in Amazon DynamoDB, then you can definitely go for Amazon Kinesis. I don't see any better option for these other than Amazon Kinesis. You can use Amazon Kinesis Data Analytics Tool to detect an anomaly before you process the data. That's one more beauty. The…
Akinola McLean
Chapter Lead - Data and Infrastructure (Head of Department) at a tech services company with 51-200 employees
Real User
Top 10
Enables us to respond in real time; great auto-scaling feature

What is our primary use case?

Our primary use case of this solution is as an intricate part of our data pipeline to deal with all of our big data problems. The traffic in our industry is highly volatile. At any given time we could have 10,000 users, and five minutes later it could be 100,000. We need systems fast enough to deal with that elasticity of demand, and the ability to deal with all the big data problems. Volume, velocity, ferocity, things like that. That's where we use the Kinesis platform. They have different iterations of it. The normal Kinesis Stream, is a little bit more manual, but we use that for our legacy… more »

Pros and Cons

  • "Great auto-scaling, auto-sharing, and auto-correction features."
  • "Lacks first in, first out queuing."

What other advice do I have?

It's important to think about how you are going to fix the end points that connect to your Kinesis files. I would rate this solution a nine out of 10.
RQ
Big Data Architect
Real User
Top 10
Great for large environments and has good configuration but needs and experienced person to set it up

What is our primary use case?

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.

Pros and Cons

  • "The solution works well in rather sizable environments."
  • "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."

What other advice do I have?

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.
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