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."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."
"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."
"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."
"Important features include that it comprises lots of functionality to connect data from various sources through connector availability, scheduling pipelines at any time, and integration with third-party and security solutions for encryption."
"The best feature that I really like is the integration."
"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 most valuable features are the option of integration with a variety of protocols, languages, and origins."
"The Ease of configuration for pipes is amazing. It has a lot of connectors. Mainly, we can do everything with the data in the pipe. I really like the graphical interface too"
"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."
"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 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."
"If you use JDBC Lookup, for example, it generally takes a long time to process data."
"Visualization and monitoring need to be improved and refined."
"Sometimes, when we have large amounts of data that is very efficiently stored in Hadoop or Kafka, it is not very efficient to run it through StreamSets, due to the lack of efficiency or the resources that StreamSets is using."
"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."
"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 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."
"One thing that I would like to add is the ability to manually enter data. The way the solution currently works is we don't have the option to manually change the data at any point in time. Being able to do that will allow us to do everything that we want to do with our data. Sometimes, we need to manually manipulate the data to make it more accurate in case our prior bifurcation filters are not good. If we have the option to manually enter the data or make the exact iterations on the data set, that would be a good thing."
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Ab Initio Co>Operating System is ranked 28th in Data Integration with 2 reviews while StreamSets is ranked 8th in Data Integration with 24 reviews. Ab Initio Co>Operating System is rated 9.6, while StreamSets is rated 8.4. The top reviewer of Ab Initio Co>Operating System writes "High performance and flexible solution for companies with large amounts of data". On the other hand, the top reviewer of StreamSets writes "We no longer need to hire highly skilled data engineers to create and monitor data pipelines". Ab Initio Co>Operating System is most compared with SSIS, Collibra Catalog, AWS Glue, Informatica Cloud Data Integration and Talend Data Management Platform, whereas StreamSets is most compared with Fivetran, Azure Data Factory, Informatica PowerCenter, SSIS and IBM InfoSphere DataStage. See our Ab Initio Co>Operating System vs. StreamSets report.
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