We performed a comparison between Hitachi Lumada Data Integration and Mule Anypoint Platform based on real PeerSpot user reviews.
Find out in this report how the two Data Integration Tools solutions compare in terms of features, pricing, service and support, easy of deployment, and ROI."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."
"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 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."
"It has a really friendly user interface, which is its main feature. The process of automating or combining SQL code with some databases and doing the automation is great and really convenient."
"The way it has improved our product is by giving our users the ability to do ad hoc reports, which is very important to our users. We can do predictive analysis on trends coming in for contracts, which is what our product does. The product helps users decide which way to go based on the predictive analysis done by Pentaho. Pentaho is not doing predictions, but reporting on the predictions that our product is doing. This is a big part of our product."
"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."
"The graphical nature of the development interface is most useful because we've got people with quite mixed skills in the team. We've got some very junior, apprentice-level people, and we've got support analysts who don't have an IT background. It allows us to have quite complicated data flows and embed logic in them. Rather than having to troll through lines and lines of code and try and work out what it's doing, you get a visual representation, which makes it quite easy for people with mixed skills to support and maintain the product. That's one side of it."
"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."
"The fact that it's a low-code solution is valuable. It's good for more junior people who may not be as experienced with programming."
"I absolutely love Hitachi. I'm one of the forefront supporters of Hitachi for my firm. It's so easy to integrate within our environments. In terms of being able to quickly build ETL jobs, transform, and then automate them, it's really easy to integrate throughout for data analytics."
"Lumada has allowed us to interact with our employees more effectively and compensate them properly. One of the cool things is that we use it to generate commissions for our salespeople and bonuses for our warehouse people. It allows us to get information out to them in a timely fashion. We can also see where they're at and how they're doing."
"Customers can make use of Runtime Fabric, an RTF environment."
"The ability to define multi-tiered APIs and reuse them is a fantastic platform feature."
"The initial setup is quite easy because the solution has a good interface through which the configuration, mapping, and so on can be done."
"The API toolkit is the solution's most valuable aspect at this time, for our organization."
"Mule Anypoint Platform is our preferred platform for integration."
"It has improved our organization a lot because of the increase in productivity, and it has simplified the development of products. MuleSoft Anypoint Platform is a highly effective tool where you can build integrations so effectively. If you establish the integration platform, it increases productivity. It helps us to do effective re-authentication, and it speeds the integration."
"This is a good platform for designing, flowing out APIs, and then doing API-based integrations."
"Overall, it is a pretty good product. It is also very scalable."
"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."
"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, 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 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."
"Its basic functionality doesn't need a whole lot of change. There could be some improvement in the consistency of the behavior of different transformation steps. The software did start as open-source and a lot of the fundamental, everyday transformation steps that you use when building ETL jobs were developed by different people. It is not a seamless paradigm. A table input step has a different way of thinking than a data merge step."
"I would like to see improvements made for real-time data processing."
"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."
"Parallel execution could be better in Pentaho. It's very simple but I don't think it works well."
"I have been facing some difficulties when working with large datasets. It seems that when there is a large amount of data, I experience memory errors."
"In the Community edition, it would be nice to have more modules that allow you to code directly within the application. It could have R or Python completely integrated into it, but this could also be because I'm using an older version."
"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."
"The stability could be better."
"The terms of use and how it's priced has become very difficult to manage, which is forcing us to look for alternatives already - and we haven't even been using it for that long just yet."
"The platform's data integration tools need improvement on the processing side."
"I would like to see some data integration and automation."
"What I hear from my customers is that it's very expensive compared to the cost of other integration suites. The cost keeps increasing. MuleSoft should come up with customization factors by using a different way of getting the cost-related stuff to attract customers. That is, they should come up with some cost optimizations."
"Code quality, Code Security, SaaS, and DaaS security, can all be improved."
"We would like an entire DevOps in place in this particular solution."
"Its documentation needed a little bit of work to make it more usable. It is a platform that is used mainly by developers and other people for connecting systems. Its documentation was confusing in some areas and was not very helpful in other areas. I had to go to a consultant to get some work done, which ideally shouldn't be required."
More Hitachi Lumada Data Integration Pricing and Cost Advice →
Hitachi Lumada Data Integration is ranked 6th in Data Integration Tools with 26 reviews while Mule Anypoint Platform is ranked 1st in Business-to-Business Middleware with 18 reviews. Hitachi Lumada Data Integration is rated 7.8, while Mule Anypoint Platform 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 Mule Anypoint Platform writes "Constantly improving to help connect applications, data, and devices". Hitachi Lumada Data Integration is most compared with SSIS, Talend Open Studio, Oracle Data Integrator (ODI) and Informatica Enterprise Data Catalog, whereas Mule Anypoint Platform is most compared with SAP Process Orchestration, Oracle Integration Cloud Service, TIBCO BusinessWorks, Mule ESB and MuleSoft Composer. See our Hitachi Lumada Data Integration vs. Mule Anypoint Platform report.
See our list of best Data Integration Tools vendors.
We monitor all Data Integration Tools reviews to prevent fraudulent reviews and keep review quality high. We do not post reviews by company employees or direct competitors. We validate each review for authenticity via cross-reference with LinkedIn, and personal follow-up with the reviewer when necessary.
