AWS Glue vs Amazon Data Firehose comparison

Amazon Data Firehose and AWS Glue are both solutions in the Cloud Data Integration category. Amazon Data Firehose is ranked #18 with an average rating of 9.0, while AWS Glue is ranked #1 with an average rating of 7.6. Amazon Data Firehose holds a 1.1% mindshare in CDI, compared to AWS Glue’s 8.2% mindshare. Additionally, 100% of Amazon Data Firehose users are willing to recommend the solution, compared to 90% of AWS Glue users who would recommend it.

Amazon Data Firehose

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580 Views
452 Comparison Views

100% willing to recommend

AWS Glue

Read 50 AWS Glue reviews

7,224 Views
4,985 Comparison Views

90% willing to recommend

Amazon Data Firehose

AWS Glue

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Executive Summary

We performed a comparison between AWS Glue and Amazon Data Firehose based on real PeerSpot user reviews.

Find out what your peers are saying about Amazon Web Services (AWS), Informatica, Salesforce and others in Cloud Data Integration.

To learn more, read our detailed Cloud Data Integration Report (Updated: March 2026).

Buyer's Guide

Cloud Data Integration

March 2026

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Review summaries and opinions

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Categories and Ranking

Amazon Data Firehose

Ranking in Cloud Data Integration

18th

Average Rating

9.0

Reviews Sentiment

8.1

Number of Reviews

Ranking in other categories

No ranking in other categories

AWS Glue

Ranking in Cloud Data Integration

1st

Average Rating

7.8

Reviews Sentiment

6.9

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of April 2026, in the Cloud Data Integration category, the mindshare of Amazon Data Firehose is 1.1%, up from 0.8% compared to the previous year. The mindshare of AWS Glue is 8.2%, down from 20.1% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Integration Mindshare Distribution
Product	Mindshare (%)
AWS Glue	8.2%
Amazon Data Firehose	1.1%
Other	90.7%

Cloud Data Integration

Featured Reviews

Johnny Suleiman

MS AWS expert at Bespin Global

Enhances our AI-driven analytics projects by providing a means to manage data streaming and delivery at any scale

The primary use case of Amazon Data Firehose is for real-time streaming data, specifically for data analysis and collection purposes. It is used to extract useful data and export it for machine learning algorithms to analyze, providing real-time data streaming Amazon Data Firehose enhances our…

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Sridivya Chillappa

application security engineer at Hyperspace IT India

Efficient data integration reduces operational time and enhances metadata management

For the initial setup with AWS Glue, I find it easy to set up the data catalog and create Glue jobs using the visual editor or the visual code. Setting permission sets via IAM rules can be a bit tricky at the start, but we ensure Glue has access to AWS S3, Redshift, and other services. Once the role is configured, it runs smoothly. For advanced configurations, connecting to VPCs and setting up connections with JDBC sources takes more time compared to my cloud experience, but overall, for someone with cloud and ETL experience, the setup is manageable and well done.

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Quotes from Members

We asked business professionals to review the solutions they use. Here are some excerpts of what they said:

Pros

"The most valuable feature is its capability for real-time data streaming."

"AWS Glue's most valuable features include its transformation capabilities, which provide data quality and shape for processing in ML or AI models."

"I like its integration and ability to handle all data-related tasks."

"For ETL, I feel the performance is excellent."

"The solution helps organizations gain flexibility in defining the structure of the data."

"You do not need many frameworks to run Glue."

"I like that it's flexible, powerful, and allows you to write your own queries and scripts to get the needed transformations."

"AWS Glue's most valuable features are the data catalog, including crawlers and tables, and Glue Studio, which means you don't have to use custom code."

"The most valuable feature of AWS Glue is its ease of use and good documentation. Additionally, we can do all the transformations that we need."

More AWS Glue pros

Cons

"Amazon Data Firehose enhances our AI-driven analytics projects by providing a means to manage data streaming and delivery at any scale."

"It would be better if it were more user-friendly. The interesting thing we found is that it was a little strange at the beginning. The way Glue works is not very straightforward. After trying different things, for example, we used just the console to create jobs. Then we realized that things were not working as expected. After researching and learning more, we realized that even though the console creates the script for the ETL processes, you need to modify or write your own script in Spark to do everything you want it to do. For example, we are pulling data from our source database and our application database, which is in Aurora. From there, we are doing the ETL to transform the data and write the results into Redshift. But what was surprising is that it's almost like whatever you want to do, you can do it with Glue because you have the option to put together your own script. Even though there are many functionalities and many connections, you have the opportunity to write your own queries to do whatever transformations you need to do. It's a little deceiving that some options are supposed to work in a certain way when you set them up in the console, but then they are not exactly working the right way or not as expected. It would be better if they provided more examples and more documentation on options."

"The mapping area and the use of the data catalog from Glue could be better."

"There should be more connectors for different databases."

"Not enough resources or services are available to run managed Spark jobs within the solution."

"In the building and deployment aspects, there is room for improvement. The current process is a bit complicated and could benefit from being more user-friendly and simpler, which would help speed up the deployment process."

"The technical support for this solution could be improved."

"When there is a need to configure connections to different database sources in respect of the target, it would be good if it were easier to deal with roles."

"Overall, I consider the technical support to be fine, although the response time could be faster in certain cases."

More AWS Glue cons

Pricing and Cost Advice

Information not available

"If you are using the solution for an enterprise business, it will be expensive."

"AWS Glue uses a pay-as-you-go approach which is helpful. The price of the overall solution is low and is a great advantage."

"The current cost is around forty to fifty thousand a month."

"The overall cost of AWS Glue could be better. It cost approximately $1,000 a month. There is paid support available from AWS Glue."

"I rate the tool an eight on a scale of one to ten, where one is expensive, and ten is expensive."

"I rate pricing an eight out of ten."

"It is not expensive. AWS Glue works on the serverless architecture. We get charged for the time the server is up. For our use case, we have to use it once in a day, and it is not expensive for us."

"AWS Glue is a high-priced solution that bills the client $150,000 to $250,000 annually."

More AWS Glue pricing and cost advice

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Top Industries

By visitors reading reviews

No data available

Financial Services Firm

19%

Computer Software Company

Manufacturing Company

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

By reviewers
Company Size	Count
Small Business	11
Midsize Enterprise	6
Large Enterprise	32

Questions from the Community

What is your experience regarding pricing and costs for Amazon Data Firehose?

The pricing is fair and balanced for the capabilities provided by Amazon Data Firehose.

See all answers

What needs improvement with Amazon Data Firehose?

There is no specific improvement mentioned for Amazon Data Firehose itself. However, it was noted that there could be room for a better understanding of real-time data streaming concepts for junior...

See all answers

What is your primary use case for Amazon Data Firehose?

See all answers

How do you select the right cloud ETL tool?

AWS Glue and Azure Data factory for ELT best performance cloud services.

See all answers

How does Talend Open Studio compare with AWS Glue?

We reviewed AWS Glue before choosing Talend Open Studio. AWS Glue is the managed ETL (extract, transform, and load) from Amazon Web Services. AWS Glue enables AWS users to create and manage jobs in...

See all answers

What are the most common use cases for AWS Glue?

AWS Glue's main use case is for allowing users to discover, prepare, move, and integrate data from multiple sources. The product lets you use this data for analytics, application development, or ma...

See all answers

Comparisons

AWS Database Migration Service vs Amazon Data Firehose

Compared 29% of the time

Denodo vs Amazon Data Firehose

Compared 10% of the time

Palantir Foundry vs Amazon Data Firehose

Compared 8% of the time

More Amazon Data Firehose Competitors

AWS Database Migration Service vs AWS Glue

Compared 39% of the time

Informatica Intelligent Data Management Cloud (IDMC) vs AWS Glue

Compared 6% of the time

SSIS vs AWS Glue

Compared 5% of the time

Palantir Foundry vs AWS Glue

Compared 4% of the time

SnapLogic vs AWS Glue

Compared 3% of the time

More AWS Glue Competitors

Product Reports

Buyer's Guide

Cloud Data Integration

March 2026

Download Amazon Data Firehose product report

Buyer's Guide

AWS Glue

April 2026

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Overview

Amazon Data Firehose offers a robust data streaming service that simplifies integration and data capture, enabling real-time data processing and analysis efficiently.

Amazon Data Firehose is a cloud-based service providing real-time data streaming into analytics tools like Amazon S3 and Redshift. It offers seamless scalability, enabling consistent delivery, transformation, and enriching capabilities of data streams. Users value its reliability for handling streaming data with minimal administration. It excels in performance for those seeking efficient data management. Still, there is room for enhancement in its pricing model to better cater to businesses with rapid fluctuations in data volume.

What are the key features of Amazon Data Firehose?

Data Transformation: Convert incoming data before delivering to destinations.
Automatic Scaling: Dynamically adjust to handle up to gigabytes of streaming data per second.
Destination Flexibility: Directly integrate with Amazon S3, Redshift, and Elasticsearch.
Data Formatting: Supports compression and format conversions.

What benefits should users expect from Amazon Data Firehose?

Efficient Data Handling: Secure and efficient real-time data processing.
Cost-Effective: Reduces infrastructure and management costs.
Simplified Integration: Easily integrates with storage and analytics services.
Consistent Performance: Reliable delivery even under high data loads.

Amazon Data Firehose finds diverse applications across industries like finance, healthcare, and e-commerce. In finance, it supports fraud detection via real-time data ingestion. Healthcare facilities use it for efficient patient monitoring systems. E-commerce platforms leverage its capabilities for real-time analytics, enhancing customer experiences with tailored offerings.

Amazon Web Services (AWS)

AWS Glue is a serverless cloud data integration tool that facilitates the discovery, preparation, movement, and integration of data from multiple sources for machine learning (ML), analytics, and application development. The solution includes additional productivity and data ops tooling for running jobs, implementing business workflows, and authoring.

AWS Glue allows users to connect to more than 70 diverse data sources and manage data in a centralized data catalog. The solution facilitates visual creation, running, and monitoring of extract, transform, and load (ETL) pipelines to load data into users' data lakes. This Amazon product seamlessly integrates with other native applications of the brand and allows users to search and query cataloged data using Amazon EMR, Amazon Athena, and Amazon Redshift Spectrum.

The solution also utilizes application programming interface (API) operations to transform users' data, create runtime logs, store job logic, and create notifications for monitoring job runs. The console of AWS Glue connects all of these services into a managed application, facilitating the monitoring and operational processes. The solution also performs provisioning and management of the resources required to run users' workloads in order to minimize manual work time for organizations.

AWS Glue Features

AWS Glue groups its features into four categories - discover, prepare, integrate, and transform. Within those groups are the following features:

Automatic schema discovery: AWS Glue crawlers connect to the organization's source or target data source through a prioritized list of classifiers to determine the schema for users' data. This feature creates metadata in companies' AWS Glue Data Catalog.
Schemas for data stream management: The AWS Glue Schema Registry enables users to validate and control the evolution of streaming data through registered Apache Avro schemas for no additional charge.
Automatic scaling based on workload: This feature dynamically scales resources up and down based on workload. The feature controls job resources, removing them depending on how much the workload can be split up.
FindMatches: This feature is for machine learning-based data deduplication and cleansing, and works by finding records that are imperfect matches of each other to remove useless data copies.
Edit, debug, and test ETL code: This feature helps users who have chosen to interactively develop their ETL code by providing development endpoints for editing, debugging, and testing the code it generates for them.
AWS Glue DataBrew: An interactive, point-and-click visual interface for specialists to clean and normalize data without the need to write any code.
AWS Glue Interactive Sessions: This feature simplifies the development of data integration jobs by enabling data engineers to interactively prepare and explore data.
AWS Glue Studio Job Notebooks: This AWS Glue feature provides serverless notebooks with minimal setup, allowing developers to start working in a timely manner.
Complex ETL pipeline building: This feature allows the product to be invoked on a schedule, on demand, or based on an event, allowing users to start multiple jobs in parallel or specify dependencies to build complex ETL pipelines.
AWS Glue Studio: This AWS Glue feature allows users to visually transform data through a drag-and-drop interface. The product automatically generates the code for ETL processes for users' data.

AWS Glue Benefits

AWS Glue offers a wide range of benefits for its users. These benefits include:

Users of other AWS products can easily onboard with AWS Glue, as it is integrated across a wide range of the company's services.
The solution is serverless, which allows for a lower total cost of ownership.
AWS Glue offers more power for users, as it automates much of the effort in building, maintaining, and running ETL jobs.
The product allows customers to easily discover and search across all their AWS datasets through AWS Glue Data Catalog.
AWS Glue does not require additional payment for managing and enforcing schemas for data streams.
The solution facilitates the authority of scalable ETL jobs for beginners and non-coding experts through a drag-and-drop interface.

Reviews from Real Users

Mustapha A., a cloud data engineer at Jems Groupe, likes AWS Glue because it is a product that is great for serverless data transformations.

Liana I., CEO at Quark Technologies SRL, describes AWS Glue as a highly scalable, reliable, and beneficial pay-as-you-go pricing model.

Amazon Web Services (AWS)

Sample Customers

Information Not Available

bp, Cerner, Expedia, Finra, HESS, intuit, Kellog's, Philips, TIME, workday

Buyer's Guide

Cloud Data Integration

March 2026

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