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Ab Initio Co>Operating System vs StreamSets comparison

Ab Initio and IBM are both solutions in the Data Integration category. Ab Initio is ranked #31 with an average rating of 9.0, while IBM is ranked #9 with an average rating of 8.4. Ab Initio holds a 1.2% mindshare in DI, compared to IBM’s 1.7% mindshare. Additionally, 66% 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 2 Ab Initio Co>Operating System reviews
  • 2,128 Views
  • 1,136 Comparison Views
66% willing to recommend
StreamSets
Read 24 StreamSets reviews
  • 3,109 Views
  • 1,983 Comparison Views
100% willing to recommend
 

Comparison Buyer's Guide

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Executive Summary
We performed a comparison between Ab Initio Co>Operating System and StreamSets based on real PeerSpot user reviews.

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

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To learn more, read our detailed Ab Initio Co>Operating System vs. StreamSets Report (Updated: November 2024).
Buyer's Guide
Ab Initio Co>Operating System vs. StreamSets
November 2024
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Categories and Ranking

Ab Initio Co>Operating System
Ranking in Data Integration
31st
Average Rating
9.6
Reviews Sentiment
7.9
Number of Reviews
2
Ranking in other categories
Workload Automation (20th)
StreamSets
Ranking in Data Integration
9th
Average Rating
8.4
Reviews Sentiment
7.5
Number of Reviews
24
Ranking in other categories
No ranking in other categories
 

Mindshare comparison

As of November 2024, in the Data Integration category, the mindshare of Ab Initio Co>Operating System is 1.2%, up from 0.6% compared to the previous year. The mindshare of StreamSets is 1.7%, up from 1.3% compared to the previous year. It is calculated based on PeerSpot user engagement data.
Data Integration
 

Featured Reviews

RV
Excellent bulk data processing for large enterprises
Co>Operating System's most valuable feature is its ability to process bulk data effectively Co>Operating System would be improved with more integrations for less well-known technologies. In the next release, Co>Operating System should include some AI capabilities on the data governance side, like…
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Reyansh Kumar - PeerSpot reviewer
We no longer need to hire highly skilled data engineers to create and monitor data pipelines
The things I like about StreamSets are its * overall user interface * efficiency * product features, which are all good. Also, 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. You just need to configure the data sources, the paths and their configurations, and you are ready to go. It is very efficient and very easy to use for ETL pipelines. It is a GUI-based interface in which you can easily create or design your own data pipelines with just a few clicks. As for moving data into modern analytics systems, we are using it with Microsoft Power BI, AWS, and some on-premises solutions, and it is very easy to get data from StreamSets into them. No hardcore coding or special technical expertise is required. It is also a no-code platform in which you can configure your data sources and data output for easy configuration of your data pipeline. This is a very important aspect because if a tool requires code development, we need to hire software developers to get the task done. By using StreamSets, it can be done with a few clicks.
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

"Co>Operating System's most valuable feature is its ability to process bulk data effectively."
"Ab Initio reaches the highest performance and is very flexible in processing huge amounts of data."
"StreamSets Transformer is a good feature because it helps you when you are developing applications and when you don't want to write a lot of code. That is the best feature overall."
"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."
"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."
"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."
"It is a very powerful, modern data analytics solution, in which you can integrate a large volume of data from different sources. It integrates all of the data and you can design, create, and monitor pipelines according to your requirements. It is an all-in-one day data ops solution."
"In StreamSets, everything is in one place."
"What I love the most is that StreamSets is very light. It's a containerized application. It's easy to use with Docker. If you are a large organization, it's very easy to use Kubernetes."
"For me, the most valuable features in StreamSets have to be the Data Collector and Control Hub, but especially the Data Collector. That feature is very elegant and seamlessly works with numerous source 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."
"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."
"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."
"The data collector in StreamSets has to be designed properly. For example, a simple database configuration with MySQL DB requires the MySQL Connector to be installed."
"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."
"We've seen a couple of cases where it appears to have a memory leak or a similar problem."
"The design experience is the bane of our existence because their documentation is not the best. Even when they update their software, they don't publish the best information on how to update and change your pipeline configuration to make it conform to current best practices. We don't pay for the added support. We use the "freeware version." The user community, as well as the documentation they provide for the standard user, are difficult, at best."
"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."
"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."
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."
"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."
"It's not so favorable for small companies."
"StreamSets is expensive, especially for small businesses."
"The overall cost for small and mid-size organizations needs to be better."
"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."
"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."
"We are running the community version right now, which can be used free of charge."
"It's not expensive because you pay per month, and the tasks you can perform with it are huge. It's reliable and cost-effective."
More StreamSets pricing and cost advice
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Top Industries

By visitors reading reviews
Financial Services Firm
39%
Computer Software Company
8%
Insurance Company
8%
University
6%
Financial Services Firm
17%
Computer Software Company
13%
Manufacturing Company
8%
Insurance Company
6%
 

Company Size

By reviewers
Large Enterprise
Midsize Enterprise
Small Business
No data available
 

Questions from the Community

What do you like most about Ab Initio Co>Operating System?
Co>Operating System's most valuable feature is its ability to process bulk data effectively.
See all answers
What needs improvement with Ab Initio Co>Operating System?
Co>Operating System would be improved with more integrations for less well-known technologies. In the next release, Co>Operating System should include some AI capabilities on the data governa...
See all answers
What advice do you have for others considering Ab Initio Co>Operating System?
Co>Operating System is best suited for big enterprises. I would rate it nine out of ten.
See all answers
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
November 2024
Ab Initio Co>Operating System reportDownload Ab Initio Co>Operating System product report
Buyer's Guide
StreamSets
October 2024
StreamSets reportDownload StreamSets product report
 

Also Known As

Co>Operating System
No data available
 

Learn More

Video not available
Ab Initio
Video not available
IBM
 

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.

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.

 

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
November 2024
Free Report: Ab Initio Co>Operating System vs. StreamSets
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