We performed a comparison between Oracle Data Integrator (ODI) 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."It's completely user-friendly."
"One of the standout features of ODI is its ability to prepare everything on a vertical level and create reusable components, which adds to its value."
"The CAEM is very useful in its modularity and portability."
"What I found most valuable in Oracle Data Integrator (ODI) is that it integrates well with almost all technologies currently being used in my company."
"The scalability is great. It's one of the reasons we chose the solution."
"The initial setup is easy."
"ODI's most valuable features are it utilizes the database engine and is very lightweight."
"The tool improved our data integration workflow primarily due to its compatibility with Oracle. Its integration makes it very convenient for analytics. Its most valuable feature is robust extended capability. The solution's debugging capabilities are good."
"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 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."
"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."
"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."
"The most valuable feature is the pipelines because they enable us to pull in and push out data from different sources and to manipulate and clean things up within them."
"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 UI is user-friendly, it doesn't require any technical know-how and we can navigate to social media or use it more easily."
"The most valuable features are the option of integration with a variety of protocols, languages, and origins."
"At present, when multiple steps are executed in parallel in the load plan and errors occur, the error handling mechanism does not function correctly."
"Technical Support could be better."
"Reverse engineering is complicated and challenging to manage."
"An area for improvement would be the lack of SQL compatibility - ODI has no ability to interact with SQL unstructured types and data types."
"I rate it a seven out of 10 because there is room for growth because ODI is still new, in comparison to Informatica, which is a mature product."
"The performance of the user interface is in need of improvement."
"It lacks a suite of tools suitable for fully processing data and moving it into decision support warehouses."
"ODI could improve by focusing on streamlining its features without unnecessary overhead."
"One area for improvement could be the cloud storage server speed, as we have faced some latency issues here and there."
"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 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."
"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."
"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."
"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."
"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."
"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."
Oracle Data Integrator (ODI) is ranked 4th in Data Integration with 67 reviews while StreamSets is ranked 8th in Data Integration with 24 reviews. Oracle Data Integrator (ODI) is rated 8.2, while StreamSets is rated 8.4. The top reviewer of Oracle Data Integrator (ODI) writes "Straightforward to implement, scalable, and has good stability and documentation, but technical support could still be improved". 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". Oracle Data Integrator (ODI) is most compared with Oracle Integration Cloud Service, SSIS, Informatica PowerCenter, Azure Data Factory and Oracle GoldenGate, whereas StreamSets is most compared with Fivetran, Azure Data Factory, Informatica PowerCenter, SSIS and Oracle GoldenGate. See our Oracle Data Integrator (ODI) vs. StreamSets report.
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