Amazon Kinesis Data Firehose Reviews & Product Details

Most of the infrastructure, basically some configurations like monitoring the pipelines, receiving notifications or alert messages, status etc... are managed by the service provider.

Fairly an easy learning curve to build pipelines with good scaling capabilities as your data needs increase. Everything is secured and regulated with the necessary compliances too. Review collected by and hosted on G2.com.

I feel the pipelines fail or there is a downtime crash that happens sometimes. The Data Pipelines you build should be good enough to run efficiently. Takes a steep learning curve when you use it for real-time data processing as it needs a higher understanding and expertise to be able to handle that. No as fast when it comes to real-time processing. Review collected by and hosted on G2.com.

One of the best features of Amazon Kinesis is its 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. Review collected by and hosted on G2.com.

There is very less visibility when the data is within AWS Kinesis. The user of the data has no idea where it resides. This is especially important in situations where there are drops in messages. Although it's not an exact science Kinesis can make it better. Review collected by and hosted on G2.com.

Its fully managed infrastructure services allow developers to focus on building applications and analysing data without worrying about the underlying infrastructure. The best part about this product is the Pay-as-you-Go-Pricing model, which means you only pay for the data you process and deliver. This makes it a cost-effective solution for handling real-time streaming data. Review collected by and hosted on G2.com.

Some downsides include limited control over delivery timing, affecting real-time delivery systems. It also has limited destinations , primarily focusing on integration with other AWS services. This makes it not compatible with other destinations, and we have to use different services to handle the integration Review collected by and hosted on G2.com.

Scalability: Amazon Kinesis Data Firehose can handle any amount of streaming data, and it automatically scales up or down based on the volume of data ingested.

Low Latency: With Amazon Kinesis Data Firehose, you can receive and process data in real-time, with a latency of just a few seconds.

Easy to use: Amazon Kinesis Data Firehose is a fully managed service, which means that you don't need to worry about managing servers, configuring and scaling infrastructure, or setting up monitoring and alerting. You can focus on processing and analyzing your data.

Integration with other AWS services: Amazon Kinesis Data Firehose seamlessly integrates with other AWS services such as S3, Redshift, Elasticsearch, and Lambda, which makes it easy to build end-to-end data processing pipelines.

Security and Compliance: Amazon Kinesis Data Firehose is designed to be highly secure and compliant with industry standards and regulations such as HIPAA, PCI, and SOC. It uses encryption in transit and at rest, and provides access controls and auditing capabilities.

Overall, Amazon Kinesis Data Firehose is a powerful tool for ingesting and processing real-time streaming data, and it can help you build scalable, secure, and compliant data processing pipelines in the AWS cloud. Review collected by and hosted on G2.com.

Cost: Amazon Kinesis Data Firehose can be expensive, especially if you are ingesting a large volume of data or using multiple destinations. You should carefully monitor and optimize your usage to avoid unexpected charges.

Complexity: While Amazon Kinesis Data Firehose is designed to be easy to use, it can still be complex to set up and manage, especially if you are new to real-time streaming data processing. You may need to invest time and resources in learning how to use the service effectively.

Availability: Like any cloud service, Amazon Kinesis Data Firehose may experience occasional downtime or disruptions, which can affect your data processing pipeline. You should design your pipeline to be resilient and have backup plans in case of failures.

Compatibility: Amazon Kinesis Data Firehose may not be compatible with all data sources or destinations, or may require additional configuration or customization to work properly with certain systems. You should check the compatibility and requirements of your data sources and destinations before using the service.

Overall, while Amazon Kinesis Data Firehose has many benefits, it is important to be aware of the potential challenges and limitations and to plan accordingly to ensure a successful implementation. Review collected by and hosted on G2.com.

- seamlessly integration

- data transformation

- easily set up data delivery pipelines

-simplifies the process of ingesting and delivering real-time streaming data Review collected by and hosted on G2.com.

-expects data in a specific format (e.g., JSON, CSV) and may require some preprocessing if your data doesn't adhere to these formats. Review collected by and hosted on G2.com.

It is best used to analyse data in a efficient manner. For me I use it to ETL the data and create bunch of graphs through tableau-kinesis driver and work on it. Review collected by and hosted on G2.com.

I do not have anything to dislike about his software as my work is going on smoothly but I would like to say that if the software was a little bit faster with tableau that could be a plus point. Review collected by and hosted on G2.com.

- It is a reliable service

- It integrates very well with other AWS solutions (lambdas, data streams, etc.)

- Easy to set up and maintain

- It gives almost real-time data delivery. Review collected by and hosted on G2.com.

- Documentation is a bit confusing, but plenty of forums exist to deal with it.

- The pricing is a little higher than other alternatives in the market.

- There is no queue system, then it could be a problem in some scenarios. Review collected by and hosted on G2.com.

Amazon Kinesis Data Firehose is a fully managed service for loading streaming data into data stores and analytics tools. It is part of the Amazon Kinesis service family and is intended to handle real-time data streams at scale.

The ease of use of Kinesis Data Firehose is one of its primary advantages. Users can create data streams in the AWS Management Console with a few clicks, and the service will handle tasks like buffering, compressing, and transforming the data before it is loaded into the destination. Kinesis Data Firehose also integrates with a number of AWS services, including Amazon S3, Amazon Redshift, and Amazon Elasticsearch, making it simple to load data into these services for further analysis.

Scalability is another important feature of Kinesis Data Firehose. The service can handle large amounts of streaming data and automatically scales to handle data volume spikes without user intervention. This means that organizations can use Kinesis Data Firehose to capture and process data from various sources, such as IoT devices, social media feeds, and web logs, and then store that data for later analysis. Review collected by and hosted on G2.com.

1. Amazon Kinesis Data Firehose has limited integration with other third-party applications and services.

2. Amazon S3, Amazon Redshift, and Amazon Elasticsearch are among the destinations supported by Kinesis Data Firehose. This can be limiting for users who want to visit other places.

3.The cost of Kinesis Data Firehose can be expensive, especially when dealing with large volumes of data.

4. Kinesis Data Firehose doesn't provide real-time processing capabilities. Data must be buffered before it can be processed and delivered to the destination. Review collected by and hosted on G2.com.

It is automatically scalable and very low cost. It is almost real time. No need to provision. It's highly customizable, and Data is typically made available in a stream for 24 hours, but for an additional cost, users can gain data availability for up to seven days. Review collected by and hosted on G2.com.

The downside is the almost real time, which means sometimes it takes longer like 60 seconds to process your data Review collected by and hosted on G2.com.

Best thing about Amazon Kinesis Data Firehose is its automatic scaling management in the gigabytes per second range and support for batching ,encryption, etc of data. Review collected by and hosted on G2.com.

Dislike about Amazon Kinesis Data Firehose is it only supports maximum data write total of 1MB per second. Batch size and throughput need to improve. Review collected by and hosted on G2.com.