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 #17 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 1.2% mindshare in CDI, compared to AWS Glue’s 18.6% 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

Read 1 Amazon Data Firehose review

156 Views
104 Comparison Views

100% willing to recommend

AWS Glue

Read 49 AWS Glue reviews

5,643 Views
2,804 Comparison Views

90% willing to recommend

Amazon Data Firehose

AWS Glue

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Executive Summary

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

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To learn more, read our detailed Cloud Data Integration Report (Updated: June 2025).

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Cloud Data Integration

June 2025

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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

17th

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

7.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of July 2025, in the Cloud Data Integration category, the mindshare of Amazon Data Firehose is 1.2%, up from 0.0% compared to the previous year. The mindshare of AWS Glue is 18.6%, down from 22.2% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Integration

Featured Reviews

Johnny Suleiman

MS AWS expert at Bespin Global MEA, an e& enterprise Company

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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Saurabh Jaiswal

Python AWS & AI Expert at a tech consulting company

Enables seamless integration and data preparation with robust transformation capabilities

AWS Glue's most valuable features include its transformation capabilities, which provide data quality and shape for processing in ML or AI models. It offers transformation options on canvas or through ETL pipelines, notebooks, and code. Additionally, it supports data preparation, cleaning, and filtering seamlessly. AWS Glue also enhances job scheduling and orchestration capabilities, integrating with AWS Glue Studio for comprehensive data workflow management.

Read full review

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."

"The solution is stable and reliable."

"The most valuable feature of AWS Glue is scalability."

"It is a stable and scalable solution."

"Glue is a NoSQL-based data ETL tool that has some advantages over IIS and ISAs."

"AWS Glue is a good solution for developers, they have the ability to write code in different languages and other software."

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

"Its user interface is quite good. You just need to choose some options to create a job in AWS Glue. The code-generation feature is also useful. If you don't want to customize it and simply want to read a file and store the data in the database, it can generate the code for you."

"AWS Glue is very quick to start without cold starts, unlike AWS Lambda."

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."

"The solution's visual ETL tool is of no use for actual implementation."

"It is very difficult to learn the tool and remember the syntaxes comparatively."

"The start-up time is really high right now. For instance, when you start up a new job, you have to wait for five or eight minutes before it starts. If the start-up time is reduced to one or two minutes, it will be great. It will be better to have a direct linkage to Redshift in AWS. If we can use data catalogs from Redshift, it will be so easy to create some data catalogs. Currently, we can only use data catalogs from S3."

"AWS Glue would be improved by making it easier to switch from single to multi-cloud."

"There could be an enhanced way of managing pure metadata management or data cataloging."

"I haven't looked into Glue in terms of seeking out flaws. I've not come across missing features."

"Only people who can code, either in Java or Python, can use the product freely. Those who don't know Java or Python might find using AWS Glue difficult."

"Beginners need additional support as it currently lacks some features required for complex transformations, often necessitating custom Python coding."

More AWS Glue cons

Pricing and Cost Advice

Information not available

"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."

"I rate the tool's pricing a four out of ten."

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

"AWS Glue follows a pay-as-you-go model, wherein the cost of the data you use will be counted as a monthly bill."

"I rate pricing an eight out of ten."

"Its price is good. We pay as we go or based on the usage, which is a good thing for us because it is simple to forecast for the tool. It is good in terms of the financial planning of the company, and it is a good way to estimate the cost. It is also simple for our clients. In my opinion, it is one of the best tools in the market for ETL processes because of the fact that you pay as you use, which separates it from other big tools such as PowerCenter, Pentaho Data Integration, and Talend."

"The solution's pricing is based on DPUs so it is a good idea to optimize use or it can get expensive."

"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."

More AWS Glue pricing and cost advice

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Top Industries

By visitors reading reviews

No data available

Financial Services Firm

21%

Computer Software Company

13%

Manufacturing Company

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

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 43% of the time

More Amazon Data Firehose Competitors

AWS Database Migration Service vs AWS Glue

Compared 32% of the time

SSIS vs AWS Glue

Compared 6% of the time

SnapLogic vs AWS Glue

Compared 5% of the time

Talend Open Studio vs AWS Glue

Compared 5% of the time

Confluent vs AWS Glue

Compared 3% of the time

More AWS Glue Competitors

Product Reports

Buyer's Guide

Cloud Data Integration

June 2025

Download Amazon Data Firehose product report

Buyer's Guide

AWS Glue

June 2025

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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

June 2025

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