AWS Glue vs Rivery comparison

Amazon Web Services (AWS) and Rivery are both solutions in the Cloud Data Integration category. Amazon Web Services (AWS) is ranked #1 with an average rating of 7.6, while Rivery is ranked #19 with an average rating of 8.0. Amazon Web Services (AWS) holds a 18.6% mindshare in CDI, compared to Rivery’s 0.7% mindshare. Additionally, 90% of Amazon Web Services (AWS) users are willing to recommend the solution, compared to 100% of Rivery users who would recommend it.

AWS Glue

Read 49 AWS Glue reviews

5,643 Views
2,804 Comparison Views

90% willing to recommend

Rivery

Read 2 Rivery reviews

172 Views
57 Comparison Views

100% willing to recommend

AWS Glue

Rivery

Comparison Buyer's Guide

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Executive SummaryUpdated on Dec 3, 2024

AWS Glue and Rivery are competing platforms in the data integration and ETL space. Rivery seems to outperform in user satisfaction, especially in terms of usability and scalability.

Features: AWS Glue provides automated ETL tasks, a serverless architecture, and seamless integration with other AWS services, enhancing data processing capabilities. Rivery offers intuitive data pipelines, pre-built data connectors, and real-time data processing, suitable for rapid deployment and agile operations. The difference lies in Glue's focus on automation versus Rivery's emphasis on ease of use and flexibility.

Ease of Deployment and Customer Service:AWS Glue requires deep integration within the AWS ecosystem, which can be complex for those not fully engaged with AWS infrastructure. Rivery promotes easier deployment with simplified data workflows and robust support, favoring businesses seeking quick implementation without exhaustive technical overhead. Customer support is more praised in Rivery, reflecting a more responsive service experience.

Pricing and ROI: AWS Glue offers cost efficiency as part of the AWS pay-as-you-go model, encouraging scalable cost management. However, Rivery's pricing is often viewed as more transparent, providing clear ROI through comprehensive plans that align with diverse business scales. Despite Glue's pricing flexibility, Rivery is seen as delivering high value, perceived as worth the setup costs by facilitating higher operational efficiency.

To learn more, read our detailed AWS Glue vs. Rivery Report (Updated: June 2025).

Buyer's Guide

AWS Glue vs. Rivery

June 2025

Download the complete report

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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

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

Rivery

Ranking in Cloud Data Integration

19th

Average Rating

8.6

Reviews Sentiment

7.3

Number of Reviews

Ranking in other categories

Data Integration (35th), Migration Tools (4th), Cloud Migration (14th)

Mindshare comparison

As of July 2025, in the Cloud Data Integration category, the mindshare of AWS Glue is 18.6%, down from 22.2% compared to the previous year. The mindshare of Rivery is 0.7%, up from 0.4% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Cloud Data Integration

Featured Reviews

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.

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reviewer2335923

Senior Operations Analyst at a computer software company with 201-500 employees

Provides users with an initial setup phase, which is fairly simple to manage

I don't know what could be improved in terms of what my company was used to previously or after moving over to Rivery. I have not had much experience with platforms other than Rivery. For me, Rivalry was a way to step up from what we used. To be honest, I am not really sure what improvements could be made in Rivery. Pricing is a little steep for smaller organizations, I would say. The product's pricing model could be a little bit better. I am not aware if there are additional packages for smaller organizations, but if there are no packages available, then maybe that would be a good way to introduce something new in the tool.

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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 of AWS Glue is scalability."

"We have found it beneficial when moving data from one source to another."

"It is a stable and scalable solution."

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

"The most valuable feature for me is the visual interface of AWS Glue."

"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."

"It is a very scalable solution."

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

More AWS Glue pros

"Connects to many APIs in the market and new ones are being added all the time."

"The solution's most valuable features are that it is quick to connect and simple to use."

Cons

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

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

"It fails to handle massive databases acquired from various sources."

"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."

"Currently, it supports only two languages in the background: Python and Scala. From our customization point of view, it would be helpful if it can also support Java in the background."

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

"One area that could be improved is the ETL view. The drag-and-drop interface is not as user-friendly as some other ETL tools."

More AWS Glue cons

"Lineage and an impact analysis or logic dependency are lacking."

"Pricing is a little steep for smaller organizations, I would say. The product's pricing model could be a little bit better."

Pricing and Cost Advice

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

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

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

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

"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."

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

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

"I rate the product's pricing a five on a scale of one to ten, where one is a high price, and ten is a low price."

More AWS Glue pricing and cost advice

"I rate the tool's price as six out of ten if I consider the lowest price to be one and the highest price to be ten."

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Top Industries

By visitors reading reviews

Financial Services Firm

21%

Computer Software Company

13%

Manufacturing Company

Government

Financial Services Firm

18%

Manufacturing Company

11%

Computer Software Company

10%

Government

10%

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

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

What is your experience regarding pricing and costs for Rivery?

The tool's price can be a little steep for a small organization. I rate the tool's price as six out of ten if I consider the lowest price to be one and the highest price to be ten.

See all answers

What needs improvement with Rivery?

See all answers

What is your primary use case for Rivery?

My company has started to use the Rivery extract data from Hive. It is like a project management sort of program, and we started to use Rivery to get the data from there over into Mavenlink, so we ...

See all answers

Comparisons

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

Oracle Integration Cloud Service vs AWS Glue

Compared 5% of the time

More AWS Glue Competitors

dbt vs Rivery

Compared 56% of the time

Azure Data Factory vs Rivery

Compared 44% of the time

More Rivery Competitors

Product Reports

Buyer's Guide

AWS Glue

June 2025

Download AWS Glue product report

Buyer's Guide

Data Integration

June 2025

Download Rivery product report

Overview

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)

Rivery is a serverless, SaaS DataOps platform that empowers companies of all sizes around the world to consolidate, orchestrate, and manage internal and external data sources with ease and efficiency.

By offering comprehensive data solutions and partnering with complementary technology providers, including Google, Snowflake, Tableau, and Looker, Rivery enables data-driven companies to build the perfect ecosystems for all their data processes.

Rivery

Sample Customers

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

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Buyer's Guide

AWS Glue vs. Rivery

June 2025

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