"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."
"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."
"It is really easy to set up and the interface is easy to use."
"In StreamSets, everything is in one place."
"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 most valuable aspect of the solution is the ease of access to the data in those databases."
"The product offers very good flexibility."
"The tool is reliable, quick, and powerful."
"Its robustness is valuable. It is a full-fledged suite. We have a data warehouse model, and there are also a lot of data quality management tools. The repository and all other tools are there. So, it is a full package in terms of reporting tools."
"In terms of which features I have found most valuable, I would say the importing and exporting features. Additionally, the data sorting, categorizing and summarizing features, especially how it can summarize based on categories. These are the key features."
"The technical support is excellent."
"If you use JDBC Lookup, for example, it generally takes a long time to process data."
"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."
"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."
"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."
"I can't really recall any missing feature or general improvement that is needed. We don't really add too many new kinds of databases and therefore our needs are already met."
"The solution could use better documentation."
"One problem is accessing the data using a solution other than SAS. The SAS data, which we create in the SAS, cannot be accessed by other tools. We can't open those data in other applications. So we need to have that application in place."
"We implemented it a while ago, and we are trying to improve the data delivery performance. We are looking into how to get faster and automated reporting. We would need better designs and workflows."
"The solution is quite expensive and hard to install/configure."
"With SAS Data Management, you have to purchase an external driver, configure all of the tables for all of the data that you will extract from Salesforce. It's not a straightforward process."
SAS Access is ranked 33rd in Data Integration Tools with 1 review while SAS Data Management is ranked 15th in Data Integration Tools with 5 reviews. SAS Access is rated 9.0, while SAS Data Management is rated 7.8. The top reviewer of SAS Access writes "Great for database access with an easy installation and good scalability". On the other hand, the top reviewer of SAS Data Management writes "One-stop-shop solution for sorting, categorizing and summarizing your data". SAS Access is most compared with Toad Data Point, Mule Anypoint Platform, SSIS, Talend Open Studio and Denodo, whereas SAS Data Management is most compared with Informatica PowerCenter, Informatica Axon, Collibra Governance, Microsoft Purview and SAP Data Services.
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