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: February 2025).

Buyer's Guide

Ab Initio Co>Operating System vs. StreamSets

February 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

High performance and flexible solution for companies with large amounts of data

My primary use of this solution is in the banking sector to process financial movements and generate reports. I also use it in the risk area of banking to detect thefts and risky behaviors Ab Initio reaches the highest performance and is very flexible in processing huge amounts of data. An…

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Nantabo Jackie

Sales Manager at Soft Hostings Limited

Simplified pipelines and helped us break down data silos within our organization

The design experience when implementing batch streaming or ECL pipelines is very easy and straightforward. When we initially attempted to integrate StreamSets with Kafka, it was somewhat challenging until we consulted the documentation, after which it became straightforward. We use StreamSets to move data into modern analytics platforms. Moving the data into modern analytics platforms is still complex. It requires a lot of understanding of logic. StreamSets enables us to build data pipelines without knowing how to code. StreamSets' ability to build data pipelines without requiring us to know complex programming is very important, as it allows us to focus on our projects without spending time writing code. StreamSets' Transformer for Snowflake is simple to use for designing both simple and complex transformation logic. StreamSets' Transformer for Snowflake is extremely important to me as it helps me to connect external data sources and keep my internal workflow organized. Transformer for Snowflake's functionality is a perfect ten out of ten. It is important and cost-effective that Transformer for Snowflake is a serverless engine embedded within the platform, as without this feature, it would be very expensive. This feature helps us to sell at lower budget costs, which would otherwise be at a high cost with other servers. StreamSets has helped improve our organization. StreamSets simplified pipelines for our organization. It is easier to complete a project when we know where and how to start, and working with the team remotely makes it more efficient. This helps us to save time and be more organized when creating data pipelines. Being a structured company that produces reliable resources for our application benefits both our clients and contacts. StreamSets' built-in data drift resilience plays a part in our ETL operations. With prior knowledge, the built-in data drift resilience is very effective, but it can be challenging to implement without the preexisting knowledge. The built-in data drift resilience reduced the time it takes us to fix data drift breakages by 45 percent. StreamSets helped us break down data silos within our organization. The use of StreamSets to break down data silos enabled us to be confident in the services and products we provide, as well as the real-time streaming we offer. This has had a positive impact on our business, as it allowed us to accurately determine the analytics we need to present to stakeholders, clients, and our sources while ensuring that the process is secure and transparent. StreamSets saved us time because anyone can use StreamSets not just developers. We can save around 40 percent of our time. StreamSets' reusable assets helped us reduce workload by around 25 percent. StreamSets saved us money by not having to hire developers with specialized skills. We saved around $2,000 US. StreamSets helped us scale our data operations. Since StreamSets makes it easy to scale our data operations, it enabled us to know exactly where to start at any time. We are aware of the timeline for completing the project, and depending on our familiarity with the software, we can come up with a solution quickly.

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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."

"I have used Data Collector, Transformer, and Control Hub products from StreamSets. What I really like about these products is that they're very user-friendly. People who are not from a technological or core development background find it easy to get started and build data pipelines and connect to the databases. They would be comfortable like any technical person within a couple of weeks."

"Also, the intuitive canvas for designing all the streams in the pipeline, along with the simplicity of the entire product are very big pluses for me. The software is very simple and straightforward. That is something that is needed right now."

"In StreamSets, everything is in one place."

"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."

"The scheduling within the data engineering pipeline is very much appreciated, and it has a wide range of connectors for connecting to any data sources like SQL Server, AWS, Azure, etc. We have used it with Kafka, Hadoop, and Azure Data Factory Datasets. Connecting to these systems with StreamSets is very easy."

"The best feature that I really like is the integration."

"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 customize it to do what you need. Many other tools have started to use features similar to those introduced by StreamSets, like automated workflows that are easy to set up."

"The ETL capabilities are very useful for us. We extract and transform data from multiple data sources, into a single, consistent data store, and then we put it in our systems. We typically use it to connect our Apache Kafka with data lakes. That process is smooth and saves us a lot of time in our production systems."

More StreamSets 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."

"Visualization and monitoring need to be improved and refined."

"One area for improvement could be the cloud storage server speed, as we have faced some latency issues here and there."

"I would like to see it integrate with other kinds of platforms, other than Java. We're going to have a lot of applications using .NET and other languages or frameworks. StreamSets is very helpful for the old Java platform but it's hard to integrate with the other platforms and frameworks."

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

"The logging mechanism could be improved. If I am working on a pipeline, then create a job out of it and it is running, it will generate constant logs. So, the logging mechanism could be simplified. Now, it is a bit difficult to understand and filter the logs. It takes some time."

"They need to improve their customer care services. Sometimes it has taken more than 48 hours to resolve an issue. That should be reduced. They are aware of small or generic issues, but not the more technical or deep issues. For those, they require some time, generally 48 to 72 hours to respond. That should be improved."

"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 was painful. Also, pipeline failures were common, and data drifting wasn't addressed, which made things worse. Licensing was another issue we encountered."

"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."

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."

"Its pricing is pretty much up to the mark. For smaller enterprises, it could be a big price to pay at the initial stage of operations, but the moment you have the Seed B or Seed C funding and you want to scale up your operations and aren't much worried about the funds, at that point in time, you would need a solution that could be scaled."

"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."

"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."

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

"StreamSets Data Collector is open source. One can utilize the StreamSets Data Collector, but the Control Hub is the main repository where all the jobs are present. Everything happens in Control Hub."

"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 licensing is expensive, and there are other costs involved too. I know from using the software that you have to buy new features whenever there are new updates, which I don't really like. But initially, it was very good."

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

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

10%

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...

See all answers

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 ...

See all answers

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...

See all answers

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Product Reports

Buyer's Guide

Data Integration

March 2025

Download Ab Initio Co>Operating System product report

Buyer's Guide

StreamSets

March 2025

Download StreamSets product report

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

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

February 2025

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