"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."
"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."
"In StreamSets, everything is in one place."
"It is really easy to set up and the interface is easy to use."
"The fact that it enables us to leverage metadata to automate data pipeline templates and reuse them is definitely one of the features that we like the best. The metadata injection is helpful because it reduces the need to create and maintain additional ETLs. If we didn't have that feature, we would have lots of duplicated ETLs that we would have to create and maintain. The data pipeline templates have definitely been helpful when looking at productivity and costs."
"We use Lumada’s ability to develop and deploy data pipeline templates once and reuse them. This is very important. When the entire pipeline is automated, we do not have any issues in respect to deployment of code or with code working in one environment but not working in another environment. We have saved a lot of time and effort from that perspective because it is easy to build ETL pipelines."
"This solution allows us to create pipelines using a minimal amount of custom coding."
"The amount of data that it loads and processes is good."
"We can schedule job execution in the BA Server, which is the front-end product we're using right now. That scheduling interface is nice."
"One of the valuable features is the ability to use PL/SQL statements inside the data transformations and jobs."
"Flexible deployment, in any environment, is very important to us. That is the key reason why we ended up with these tools. Because we have a very highly secure environment, we must be able to install it in multiple environments on multiple different servers. The fact that we could use the same tool in all our environments, on-prem and in the cloud, was very important to us."
"I can create faster instructions than writing with SQL or code. Also, I am able to do some background control of the data process with this tool. Therefore, I use it as an ELT tool. I have a station area where I can work with all the information that I have in my production databases, then I can work with the data that I created."
"I like that it is a very good integration tool with many other things. TIBCO is very good for cloud integration"
"If you use JDBC Lookup, for example, it generally takes a long time to process data."
"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."
"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've seen a couple of cases where it appears to have a memory leak or a similar problem."
"I was not happy with the Pentaho Report Designer because of the way it was set up. There was a zone and, under it, another zone, and under that another one, and under that another one. There were a lot of levels and places inside the report, and it was a little bit complicated. You have to search all these different places using a mouse, clicking everywhere... each report is coded in a binary file... You cannot search with a text search tool..."
"I work with different databases. I would like to work with more connectors to new databases, e.g., DynamoDB and MariaDB, and new cloud solutions, e.g., AWS, Azure, and GCP. If they had these connectors, that would be great. They could improve by building new connectors. If you have native connections to different databases, then you can make instructions more efficient and in a more natural way. You don't have to write any scripts to use that connector."
"In terms of the flexibility to deploy in any environment, such as on-premise or in the cloud, we can do the cloud deployment only through virtual machines. We might also be able to work on different environments through Docker or Kubernetes, but we don't have an Azure app or an AWS app for easy deployment to the cloud. We can only do it through virtual machines, which is a problem, but we can manage it. We also work with Databricks because it works with Spark. We can work with clustered servers, and we can easily do the deployment in the cloud. With a right-click, we can deploy Databricks through the app on AWS or Azure cloud."
"A big problem after deploying something that we do in Lumada is with Git. You get a binary file to do a code review. So, if you need to do a review, you have to take pictures of the screen to show each step. That is the biggest bug if you are using Git."
"I would like to see support for some additional cloud sources. It doesn't support Azure, for example. I was trying to do a PoC with Azure the other day but it seems they don't support it."
"I would like to see improvements made for real-time data processing."
"If you're working with a larger data set, I'm not so sure it would be the best solution. The larger things got the slower it was."
"Since Hitachi took over, I don't feel that the documentation is as good within the solution. It used to have very good help built right in."
"Integrations could be better. Although integration is good, we have faced some block issues."
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Hitachi Lumada Data Integration is ranked 5th in Data Integration Tools with 24 reviews while TIBCO Cloud Integration is ranked 14th in Integration Platform as a Service (iPaaS) with 1 review. Hitachi Lumada Data Integration is rated 8.0, while TIBCO Cloud Integration is rated 8.0. The top reviewer of Hitachi Lumada Data Integration writes "Saves time and makes it easy for our mixed-skilled team to support the product, but more guidance and better error messages are required in the UI". On the other hand, the top reviewer of TIBCO Cloud Integration writes "A very good cloud integration tool with many other things". Hitachi Lumada Data Integration is most compared with SSIS, Talend Open Studio, Oracle Data Integrator (ODI), Informatica PowerCenter and IBM InfoSphere DataStage, whereas TIBCO Cloud Integration is most compared with SAP Process Orchestration, Microsoft Azure Logic Apps, Axway AMPLIFY Application Integration, Oracle Integration Cloud Service and Azure Data Factory.
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