Ab Initio Co>Operating System vs StreamSets comparison

Ab Initio and IBM are both solutions in the Data Integration category. Ab Initio is ranked #47, while IBM is ranked #15 with an average rating of 8.4. Ab Initio holds a 1.5% mindshare in DI, compared to IBM’s 1.6% mindshare. Additionally, 75% of Ab Initio users are willing to recommend the solution, compared to 100% of IBM 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

StreamSets

Read 21 StreamSets reviews

2,378 Views
1,645 Comparison Views

100% willing to recommend

Ab Initio Co>Operating System

StreamSets

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Executive SummaryUpdated on Dec 19, 2024

Ab Initio Co>Operating System and StreamSets compete in data management and integration, with Ab Initio often preferred for handling complex workflows due to its reliability.

Features: Ab Initio Co>Operating System offers a comprehensive suite for data processing, known for its scalability and stability in managing large datasets. StreamSets features an adaptable architecture optimized for real-time analytics, making it suitable for changing data environments. Ab Initio focuses on robust enterprise workflows, while StreamSets emphasizes agility with continuous data ingestion.

Ease of Deployment and Customer Service: StreamSets provides a simplified deployment with strong community support and cloud-native design for easy integration across environments. Ab Initio requires more structured deployment but offers reliable support services, highlighting its focus on high-assurance assistance.

Pricing and ROI: Ab Initio involves higher initial costs, yielding substantial ROI due to its powerful data processing capabilities for enterprises needing comprehensive solutions. StreamSets offers a cost-effective entry point with a compelling ROI for organizations seeking modern data pipeline management and swift deployment.

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

Buyer's Guide

Ab Initio Co>Operating System vs. StreamSets

April 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

Ab Initio Co>Operating System

Ranking in Data Integration

47th

Average Rating

9.4

Reviews Sentiment

7.9

Number of Reviews

Ranking in other categories

Workload Automation (29th)

StreamSets

Ranking in Data Integration

15th

Average Rating

8.4

Reviews Sentiment

7.0

Number of Reviews

Ranking in other categories

No ranking in other categories

Mindshare comparison

As of April 2025, in the Data Integration category, the mindshare of Ab Initio Co>Operating System is 1.5%, up from 0.6% compared to the previous year. The mindshare of StreamSets is 1.6%, up from 1.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.

Data Integration

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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Karthik Rajamani

Principal Engineer at Tata Consultancy Services

Integrates with different enterprise systems and enables us to easily build data pipelines without knowing how to code

There are a few things that can be better. We create pipelines or jobs in StreamSets Control Hub. It is a great feature, but if there is a way to have a folder structure or organize the pipelines and jobs in Control Hub, it would be great. I submitted a ticket for this some time back. There are certain features that are only available at certain stages. For example, HTTP Client has some great features when it is used as a processor, but those features are not available in HTTP Client as a destination. There could be some improvements on the group side. Currently, if I want to know which users are a part of certain groups, it is not straightforward to see. You have to go to each and every user and check the groups he or she is a part of. They could improve it in that direction. Currently, we have to put in a manual effort. In case something goes wrong, we have to go to each and every user account to check whether he or she is a part of a certain group or not.

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

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

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

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

"StreamSets data drift feature gives us an alert upfront so we know that the data can be ingested. Whatever the schema or data type changes, it lands automatically into the data lake without any intervention from us, but then that information is crucial to fix for downstream pipelines, which process the data into models, like Tableau and Power BI models. This is actually very useful for us. We are already seeing benefits. Our pipelines used to break when there were data drift changes, then we needed to spend about a week fixing it. Right now, we are saving one to two weeks. Though, it depends on the complexity of the pipeline, we are definitely seeing a lot of time being saved."

"It is really easy to set up and the interface is easy to use."

"The entire user interface is very simple and the simplicity of creating pipelines is something that I like very much about it. The design experience is very smooth."

"The most valuable would be the GUI platform that I saw. I first saw it at a special session that StreamSets provided towards the end of the summer. I saw the way you set it up and how you have different processes going on with your data. The design experience seemed to be pretty straightforward to me in terms of how you drag and drop these nodes and connect them with arrows."

"I really appreciate the numerous ready connectors available on both the source and target sides, the support for various media file formats, and the ease of configuring and managing pipelines centrally."

"In StreamSets, everything is in one place."

"StreamSets is the leader in the market."

"StreamSets’ data drift resilience has reduced the time it takes us to fix data drift breakages. For example, in our previous Hadoop scenario, when we were creating the Sqoop-based processes to move data from source to destinations, we were getting the job done. That took approximately an hour to an hour and a half when we did it with Hadoop. However, with the StreamSets, since it works on a data collector-based mechanism, it completes the same process in 15 minutes of time. Therefore, it has saved us around 45 minutes per data pipeline or table that we migrate. Thus, it reduced the data transfer, including the drift part, by 45 minutes."

More StreamSets pros

Cons

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

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

"StreamSets should provide a mechanism to be able to perform data quality assessment when the data is being moved from one source to the target."

"The execution engine could be improved. When I was at their session, they were using some obscure platform to run. There is a controller, which controls what happens on that, but you should be able to easily do this at any of the cloud services, such as Google Cloud. You shouldn't have any issues in terms of how to run it with their online development platform or design platform, basically their execution engine. There are issues with that."

"The monitoring visualization is not that user-friendly. It should include other features to visualize things, like how many records were streamed from a source to a destination on a particular date."

"In terms of the product, I don't think there is any room for improvement because it is very good. One small area of improvement that is very much needed is on the knowledge base side. Sometimes, it is not very clear how to set up a certain process or a certain node for a person who's using the platform for the first time."

"We've seen a couple of cases where it appears to have a memory leak or a similar problem."

"Currently, we can only use the query to read data from SAP HANA. What we would like to see, as soon as possible, is the ability to read from multiple tables from SAP HANA. That would be a really good thing that we could use immediately. For example, if you have 100 tables in SQL Server or Oracle, then you could just point it to the schema or the 100 tables and ingestion information. However, you can't do that in SAP HANA since StreamSets currently is lacking in this. They do not have a multi-table feature for SAP HANA. Therefore, a multi-table origin for SAP HANA would be helpful."

"Sometimes, it is not clear at first how to set up nodes. A site with an explanation of how each node works would be very helpful."

"There aren't enough hands-on labs, and debugging is also an issue because it takes a lot of time. Logs are not that clear when you are debugging, and you can only select a single source for a pipeline."

More StreamSets cons

Pricing and Cost Advice

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

"The pricing is too fixed. It should be based on how much data you need to process. Some businesses are not so big that they process a lot of data."

"StreamSets is an expensive solution."

"There are two editions, Professional and Enterprise, and there is a free trial. We're using the Professional edition and it is competitively priced."

"It has a CPU core-based licensing, which works for us and is quite good."

"There are different versions of the product. One is the corporate license version, and the other one is the open-source or free version. I have been using the corporate license version, but they have recently launched a new open-source version so that anybody can create an account and use it. The licensing cost varies from customer to customer. I don't have a lot of input on that. It is taken care of by PMO, and they seem fine with its pricing model. It is being used enterprise-wide. They seem to have got a good deal for StreamSets."

"We use the free version. It's great for a public, free release. Our stance is that the paid support model is too expensive to get into. They should honestly reevaluate that."

"The overall cost is very flexible so it is not a burden for our organization... However, the cost should be improved. For small and mid-size organizations it might be a challenge."

"The pricing is affordable for any business."

More StreamSets pricing and cost advice

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Top Industries

By visitors reading reviews

Financial Services Firm

38%

Computer Software Company

Insurance Company

University

Financial Services Firm

14%

Computer Software Company

11%

Manufacturing Company

Insurance Company

Company Size

By reviewers

Large Enterprise

Midsize Enterprise

Small Business

No data available

Questions from the Community

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What do you like most about StreamSets?

The best thing about StreamSets is its plugins, which are very useful and work well with almost every data source. It's also easy to use, especially if you're comfortable with SQL. You can customiz...

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What needs improvement with StreamSets?

We often faced problems, especially with SAP ERP. We struggled because many columns weren't integers or primary keys, which StreamSets couldn't handle. We had to restructure our data tables, which ...

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What is your primary use case for StreamSets?

StreamSets is used for data transformation rather than ETL processes. It focuses on transforming data directly from sources without handling the extraction part of the process. The transformed data...

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Product Reports

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Data Integration

March 2025

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Buyer's Guide

StreamSets

March 2025

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Also Known As

Co>Operating System

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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

StreamSets is a data integration platform that enables organizations to efficiently move and process data across various systems. It offers a user-friendly interface for designing, deploying, and managing data pipelines, allowing users to easily connect to various data sources and destinations. StreamSets also provides real-time monitoring and alerting capabilities, ensuring that data is flowing smoothly and any issues are quickly addressed.

IBM

Sample Customers

A multinational transportation company

Availity, BT Group, Humana, Deluxe, GSK, RingCentral, IBM, Shell, SamTrans, State of Ohio, TalentFulfilled, TechBridge

Buyer's Guide

Ab Initio Co>Operating System vs. StreamSets

April 2025

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