AWS Glue vs Ab Initio Co>Operating System comparison

Ab Initio and Amazon Web Services (AWS) are both solutions in the Cloud Data Integration category. Additionally, 75% of Ab Initio users are willing to recommend the solution, compared to 89% of Amazon Web Services (AWS) users who would recommend it.

Ab Initio Co>Operating System

Read 3 Ab Initio Co>Operating System reviews

1,635 Views
1,058 Comparison Views

75% willing to recommend

AWS Glue

Read 48 AWS Glue reviews

7,339 Views
5,504 Comparison Views

89% willing to recommend

Ab Initio Co>Operating System

AWS Glue

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Executive Summary

We performed a comparison between Ab Initio Co>Operating System and AWS Glue based on real PeerSpot user reviews.

Find out in this report how the two Cloud Data Integration solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI.

To learn more, read our detailed AWS Glue vs. Ab Initio Co>Operating System Report (Updated: April 2025).

Buyer's Guide

AWS Glue vs. Ab Initio Co>Operating System

April 2025

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Helped 848,253 peers since 2012

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

Ab Initio Co>Operating System

Average Rating

9.4

Reviews Sentiment

7.9

Number of Reviews

Ranking in other categories

Data Integration (47th), Workload Automation (29th)

AWS Glue

Average Rating

7.8

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

Cloud Data Integration (1st)

Featured Reviews

AlejandroMosso

Senior Solutions Architect at IDS Comercial

Enables creation of sophisticated applications with powerful parallelism and quick, effective support

The most valuable features of Ab Initio Co>Operating System are its performance and the ability to implement parallelism. There are three kinds of parallelism in Ab Initio Co>Operating System, which allow us to create very sophisticated solutions for almost any kind of application. This parallelism is one of the strongest features. Additionally, its scalability offers a unique way to escalate applications that differs from other technologies. In terms of data processing, the emphasis is on understanding the data. Data profiling is fundamental, and Ab Initio Co>Operating System integrates tools to perform this within the GDE, as well as specialized products for this purpose. Data profiling graphs can be implemented when necessary to understand the data sources.

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Muthuvel Sivaraman

AVP at a manufacturing company with 10,001+ employees

Handles a huge volume of data and is serverless, but it can be considered costly by some users

We use Amazon's services to provide technical support for the product. If you want to have support, Oracle and others offer a single support, and other tools have a direct support window. For Amazon, we need to pay 10 percent of my billing amount for the tool to get support services. Whether to raise a support ticket or not is an issue since ten percent is a huge amount. My company ends up using all the options without help from support. It is very difficult for any common man to understand why there is a need to pay ten percent for support. If I find an issue in the product, and I need to get support from AWS to fix it, then I need to pay ten percent of the tool's bill amount to Amazon. AWS is a very tricky tool because everything is evolving nowadays. AWS engineers are getting hired from other places, and even after that, if I am not getting any technical support, then things will be very nasty. There are some good engineers who help users outside the normal support cycle, but it doesn't meet their needs. I rate the technical support a four out of ten.

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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

"Ab Initio reaches the highest performance and is very flexible in processing huge amounts of data."

"Co>Operating System's most valuable feature is its ability to process bulk data effectively."

"Ab Initio Co>Operating System support is the best I have encountered."

"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 two features I find most valuable in AWS Glue are its user interface and ease of use."

"I appreciate AWS Glue for its cost-effectiveness."

"The solution's technical support is good. Whenever we raise a use case where we face an issue in our company, we get a response from the solution's technical team."

"It's very good to manage."

"The facility to integrate with S3 and the possibility to use Jupyter Notebook inside the pipeline are the most valuable features."

"The best thing about AWS Glue is its scalability and how easy it is to process a large amount of data."

"Data catalog and triggers are the two best features for me. AWS Glue has its own data catalog, which makes it great and really easy to use. Triggers are also really good for scheduling the ETL process."

More AWS Glue pros

Cons

"An awesome improvement would be big data solutions, for example, implementing some kind of business intelligence or neural networks for artificial intelligence."

"Co>Operating System would be improved with more integrations for less well-known technologies."

"The drawbacks associated with the product stem from the fact that, based on the data volume, it can become very costly."

"I have encountered challenges with multi-region support."

"AWS Glue should be more reliable and faster in processing. Enhancing the speed of data processing would be beneficial."

"The solution’s stability could be improved."

"We face performance issues when using AWS Glue for data transformation and integration."

"It is quite clunky and code-heavy, which is my biggest problem."

"Cost-wise, AWS Glue is expensive, so that's an area for improvement. The process for setting up the solution was also complex, which is another area for improvement."

"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."

More AWS Glue cons

Pricing and Cost Advice

"Co>Operating System's pricing is on the expensive end since it tends to be used by big enterprises."

"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 pricing an eight out of ten."

"This solution is affordable and there is an option to pay for the solution based on your usage."

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

"The pricing is a bit higher than other solutions like Athena and EC2. If the pricing becomes more scaled or flexible, it will be good because you have to pay 44 cents just for one DPU for an hour. If you increase DPUs to 5 or 10, the pricing gets multiplied. There are also some time limits like 0 to 10 minutes or 10 to 20 minutes. If the pricing is according to the minutes, it would be better because you have to limit your job to 10 minutes or 20 minutes."

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

"It is an expensive product. I rate its pricing a nine out of ten."

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

More AWS Glue pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

38%

Computer Software Company

10%

Insurance Company

University

Financial Services Firm

22%

Computer Software Company

14%

Manufacturing Company

Government

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

Ask a question

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What are the most common use cases for AWS Glue?

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Compared 5% of the time

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Compared 5% of the time

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Compared 4% of the time

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Product Reports

Buyer's Guide

Data Integration

March 2025

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Buyer's Guide

AWS Glue

April 2025

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Also Known As

Co>Operating System

No data available

Overview

Ab Initio Co>Operating System is used for data integration, ETL processes, and complex data transformations. It is robust in handling large-scale data processing and batch processing, offering scalability, reliability, and performance for managing heavy workloads.

Ab Initio Co>Operating System provides real-time data processing capabilities, an intuitive meta-programming environment, and efficient batch job execution. Users appreciate its flexibility in supporting various data sources and platforms. Primary use cases involve addressing complex data transformations and integration needs, enhancing productivity and efficiency.

What are the key features of Ab Initio Co>Operating System?

Scalability: Efficiently handles large-scale data processing and batch processing.
Robust Parallel Processing: Delivers powerful ETL capabilities with strong performance.
Intuitive Drag-and-Drop Interface: Simplifies creating and managing data workflows.
Flexible Data Integration: Supports diverse data sources seamlessly.
Error Handling and Debugging: Features strong tools for managing and resolving issues.
Automation: Automates repetitive tasks, streamlining operations.
Seamless Integration: Easily integrates with other tools, enhancing workflow efficiency.

What benefits and ROI should be considered?

Performance: High reliability and performance in managing heavy workloads.
Efficiency: Real-time data processing enhances productivity and decision-making.
Scalability: Efficient scaling to meet growing data processing needs.
Flexibility: Supports a wide range of data sources and platforms.
Usability: Intuitive interface and automation reduce learning curve and improve efficiency.

Industries implement Ab Initio Co>Operating System for its reliable data integration and ETL capabilities. Financial services use it for processing large volumes of transactional data, while retail sectors apply it for real-time analysis of customer data. Healthcare organizations leverage its robust processing for managing patient records and data aggregation.

Ab Initio

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

A multinational transportation company

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

Buyer's Guide

AWS Glue vs. Ab Initio Co>Operating System

April 2025

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